Systems and methods for multivariate stroke detection

ABSTRACT

A system for detecting an anomalous event in a person includes a body in contact with a skin surface of a person; a heat source for heating the skin surface to a target temperature; a skin temperature sensor for measuring a temperature of the skin surface in contact with the heat source; a blood volume sensor for measuring a blood volume of the skin surface; and a hardware processor communicatively coupled to the heat source, the blood volume sensor, the skin temperature sensor, and an environmental temperature sensor. The hardware processor is configured to receive a baseline blood volume signal, output a heating signal to the heat source to initiate a heating cycle, receive a second blood volume signal from the blood volume sensor, compare the second blood volume signal to the baseline blood volume signal, and determine whether an anomalous biologic event has occurred.

INCORPORATION BY REFERENCE

This application claims priority to U.S. Provisional Patent ApplicationNo. 62/915,269, filed on Oct. 15, 2019, and to U.S. Provisional PatentApplication No. 63/053,265, filed on Jul. 17, 2020. Each of theprovisional patent applications are hereby incorporated by referenceherein in their entireties, forming part of the present disclosure. Anyfeature, structure, material, method, or step that is described and/orillustrated in any embodiment in the foregoing provisional patentapplications can be used with or instead of any feature, structure,material, method, or step that is described in the following paragraphsof this specification and/or illustrated in the accompanying drawings.

TECHNICAL FIELD

This disclosure relates generally to the field of disease detection and,more specifically, to stroke detection.

BACKGROUND

A stroke results from the death of brain tissue due to disruptions ofblood flow to the brain. An ischemic stroke happens when there is ablockage of blood flow to the brain, usually as the result of a bloodclot. Hemorrhagic stroke happens when there is a rupture of a bloodvessel in the brain, resulting in bleeding into the brain tissue andsurrounding space.

There are many physiologic symptoms of stroke onset that vary dependingon the location of the affected tissue. Early symptoms of an evolvingstroke may be able to reduce or even resolve if the interruption ofblood flow is resolved quickly, before the tissue has died. One categoryof symptoms is disrupted vision, including blurred, dimming oftenlikened to a curtain falling) or even complete loss of vision. Strokepatients often also experience eye deviation or difficult with eyetracking.

Just as a stroke can affect the part of the brain that is associatedwith sight, it can also affect the parts of the brain that have to dowith speech, comprehension and communication. Patients suffering from astroke may exhibit slurred speech or garbled speech that renders themincomprehensible.

Another common symptom of stroke is weakness on one side of the body.This can manifest or partial or total paralysis of the side of the face,one arm, one leg, or the entire side of one's body.

Ischemic stroke is the most common type of stroke and is often painlesswhen experienced, but hemorrhagic strokes are very painful, often beingdescribed as sudden onset of “the worst headache of one's life”. Often,many people's headaches are accompanied with a feeling of dizziness,nausea, and vomiting. Smell and taste can also be impacted during theonset of a stroke.

Anything that affects the brain, from trauma to stroke, has thepotential for cognitive disablement. A feeling of confusion, or aconstant second-guessing of ones' actions, can sometimes appear daysbefore a stroke occurs.

Another common symptom of a stroke is the sudden onset of fatigue.

Stroke symptoms can vary in duration and occur with or without pain,which can make stroke detection difficult. Further, strokes can occurduring sleep, making detection even more difficult. If a stroke doesoccur while the person is sleeping, it may not wake a person up rightaway. As a result, when patients wake up symptomatic, it is unclearwhether the stroke just started or whether it has already been occurringduring sleep.

If a stroke is detected and patients seek care quickly, there are manyevidence-based interventions that can dramatically reduce the death anddisability resultant from the disease. In severe ischemic strokes, everyminute of delay to flow restoration is equated to the loss of a week ofDisability Adjusted Life Years (DALYs). Despite these treatments beingavailable, fewer than 20% of patients receive them. Even among patientsthat do receive intervention, outcomes are often suboptimal because ofthe delays to intervention. Stroke detection is difficult because strokefrequently doesn't hurt, mimics other health events, and isheterogeneous in its presentation. Improvements in detection of andcare-seeking for stroke onset could dramatically reduce the death anddisability associated with the disease.

Like stroke, COVID-19 is proving to have heterogeneous symptoms, many ofwhich resemble those of neurologic disorders. Recent publications haveshown early evidence of encephalopathies, inflammatory CNS syndromes,ischemic strokes, and peripheral neurological disorders in patientsbeing treated for COVID-19. (Zubair, JAMA Neurology, 2020) With mostCOVID-19 patients being managed remotely, and a significant percentageof inpatients requiring invasive ventilation, monitoring for the obvioussymptoms of neurological disruption may be difficult. As such,improvements in remote monitoring and care for COVID-19 patients coulddramatically reduce the death and disability associated with thedisease.

SUMMARY

One aspect of the present disclosure is directed to a wearable systemfor detecting an anomalous biologic event in a person. The systemincludes a body having a first surface opposite a second surface incontact with a skin surface of a person; a thermal stimulus source suchas a heat source or a Peltier cooler in communication with the skinsurface, such that the heat source is configured to heat the skinsurface to a target temperature; a skin temperature sensor positioned onthe second surface and configured to measure a temperature of the skinsurface in contact with the heat source; a blood volume sensorpositioned on the second surface and configured to measure a bloodvolume of the skin surface; and a hardware processor communicativelycoupled to the heat source, the blood volume sensor, the skintemperature sensor, and an environmental temperature sensor configuredto measure a temperature of the environment around the wearable system.The hardware processor is configured to: receive a baseline blood volumesignal from the blood volume sensor, output a heating signal to the heatsource to initiate a heating cycle, such that the heating cyclecomprises heating the skin surface to the target temperature, receive asecond blood volume signal from the blood volume sensor in response tothe skin surface reaching the target temperature, compare the secondblood volume signal to the baseline blood volume signal, and determinewhether an anomalous biologic event has occurred based on thecomparison.

In some embodiments, the second blood volume signal includes a set ofblood volume signals, such that the blood volume of the skin surface ismeasured repeatedly before, during, and after a heating cycle of theheat source. In some embodiments, the second blood volume signalincludes a plurality of blood volume signals, such that the blood volumeof the skin surface is measured continuously before, during, and after aheating cycle of the heat source.

In some embodiments, hardware processor is further configured to receivethe second blood volume signal after the target temperature is reached,after a predetermined length of time has expired, or after one or moreheating cycles have concluded.

In some embodiments, comparing the second blood volume signal to thebaseline blood volume signal includes calculating a baseline ratio ofalternating current (AC) to direct current (DC) for the baseline bloodvolume signal and a second ratio of AC to DC for the second blood volumesignal and comparing the baseline ratio to the second ratio.

In some embodiments, the environmental temperature sensor is positionedon the first side of the body of the wearable system.

In some embodiments, the system further includes a remote computingdevice communicative coupled to the wearable system and comprising theenvironmental temperature sensor. In some embodiments, the remotecomputing device includes one of: a laptop, cellular device, aworkstation, a server, a desktop computer, a personal digital assistant,a second wearable system or device, or a netbook.

In some embodiments, the heat source is positioned on the second surfaceof the body.

In some embodiments, the hardware processor is further configured toreceive baseline temperature signals from the skin temperature sensorand the environmental temperature sensor, determine the targettemperature based on the baseline temperature signals, and determinewhether the target temperature is below a maximum temperature value.

In some embodiments, the hardware processor is further configured tocycle the heat source to maintain the target temperature.

In some embodiments, the system further includes one or moreelectrodermal activity sensors positioned on the second surface.

In some embodiments, the one or more electrodermal activity sensors arespaced apart from the heating element by about 0.25 inches to about 4inches.

In some embodiments, the system further includes one or more motionsensors configured to measure a motion of a body portion to which thewearable system is coupled.

In some embodiments, the first and second surfaces define a cavitytherebetween to provide airflow between the first and second surfaces.

In some embodiments, the hardware processor resides on or within thefirst surface.

In some embodiments, the cavity defined by the first and second surfacesphysically separates the heat source from the hardware processor on orwithin the first surface.

In some embodiments, the cavity defined by the first and second surfaceshas sufficient volume to facilitate cooling of the heat source inbetween heating cycles.

In some embodiments, the anomalous biologic event comprises a strokeevent.

In some embodiments, the wearable system is positioned on a left limb ofa user and a second wearable system is positioned on a right limb of theuser, wherein the second wearable system comprises a second heatingelement, a second skin temperature sensor, and a second blood volumesensor, wherein the hardware processor is further configured to compareright side blood volume signals to left side blood volume signals todetermine whether the anomalous biologic event has occurred.

In some embodiments, the hardware processor is further configured tosynchronize the signals received from the left limb and the right limbin time; and compare the synchronized signals from the left limb and theright limb to determine whether the anomalous biologic event occurred.In some embodiments, the comparison takes into account a baselinedifference between the left limb and the right limb.

In some embodiments, the system further includes a tensionable bandcoupled to the body. In some embodiments, the tensionable band furtherincludes a visual indicator to indicate when one or more of: the heatingelement, the skin temperature sensor, the blood volume sensor, or acombination thereof is sufficiently coupled to the skin surface toenable accurate sensor readings. In some embodiments, one or more endsof the tensionable band are coupled to the body at a position that iscentered with respect to one or more sensors positioned on the secondsurface.

In some embodiments, the heat source is positioned concentrically aboutone or both of the blood volume sensor and the skin temperature sensor.

In some embodiments, the blood volume sensor comprises aphotoplethysmography sensor or an impedance plethysmographic sensor.

In some embodiments, the skin temperature sensor comprises athermocouple, a resistance temperature detector, a thermistor, or aninfrared temperature sensor.

In some embodiments, the system further includes a support structurecoupled to the heat source and configured to couple the heat source tothe second surface and at least partially expose the heat source to thecavity.

In some embodiments, the blood volume sensor is further configured tomeasure one or more of: heart rate, heart rate variability, or oxygensaturation.

In some embodiments, the target temperature is individualized to theuser. In some embodiments, individualization of the target temperatureincludes receiving a user input related to perceived temperature of theskin surface. In some embodiments, individualization of the targettemperature is based on signals received from the blood volume sensor.

In some embodiments, the heat source comprises one of: a heating elementor an environmental temperature.

Another aspect of the present invention is directed to a wearable systemfor detecting an anomalous biologic event in a person. The systemincludes a body having a first surface opposite a second surface incontact with a skin surface of a person, the first and second surfacesdefining a cavity therebetween to provide airflow between the first andsecond surfaces; a heating element positioned on the second surface andconfigured to heat the skin surface for a predetermined length of time;a skin temperature sensor positioned on the second surface andconfigured to measure a temperature of the skin surface in contact withthe heating element; a blood volume sensor positioned on the secondsurface and configured to measure a blood volume of the skin surface;and a hardware processor communicatively coupled to the heating element,the blood volume sensor, the skin temperature sensor, and anenvironmental temperature sensor configured to measure a temperature ofthe environment around the wearable system.

The hardware processor is configured to receive a baseline blood volumesignal from the blood volume sensor, output a heating signal to theheating element to initiate a heating cycle, such that the heating cyclecomprises heating the skin surface to a target temperature, receive asecond blood volume signal from the blood volume sensor in response tothe skin surface reaching the target temperature, compare the secondblood volume signal to the baseline blood volume signal, and determinewhether an anomalous biologic event has occurred based on thecomparison.

Another aspect of the present invention is directed to a wearable systemfor detecting an anomalous biologic event in a person. The systemincludes a body having a first surface opposite a second surface incontact with a skin surface of a person; a heat source in communicationwith the skin surface, such that the heat source is configured to heatthe skin surface to a target temperature; a skin temperature sensorpositioned on the second surface and configured to measure a temperatureof the skin surface in contact with the heat source; a sensor positionedon the second surface and configured to measure a parameter of interestof the person; and a hardware processor communicatively coupled to theheat source, the sensor, the skin temperature sensor, and anenvironmental temperature sensor configured to measure a temperature ofthe environment around the wearable system.

The hardware processor is configured to receive a baseline sensor signalfrom the sensor, output a heating signal to the heat source to initiatea heating cycle, wherein the heating cycle comprises heating the skinsurface to the target temperature, receive a second sensor signal fromthe sensor in response to the skin surface reaching the targettemperature, compare the second sensor signal to the baseline sensorsignal, and determine whether an anomalous biologic event has occurredbased on the comparison.

In some embodiments, the sensor is selected from the group consistingof: a stretch sensor, an electrodermal activity sensor, anelectrocardiogram sensor, a camera, or a blood volume sensor.

In some embodiments, the parameter of interest includes one or more of ablood pressure, a heart rate, a heart rate variability, a gaze, a facialexpression, a skin conductance response, a vasodilation response, or adilation response.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing is a summary, and thus, necessarily limited in detail. Theabove-mentioned aspects, as well as other aspects, features, andadvantages of the present technology are described below in connectionwith various embodiments, with reference made to the accompanyingdrawings.

FIG. 1A illustrates one embodiment of a multivariate system for strokedetection.

FIG. 1B illustrates another embodiment of a multivariate system forstroke detection.

FIG. 2 shows blood pressure pulse in various parts of the body.

FIG. 3 illustrates one embodiment of a wearable device for strokedetection.

FIG. 4 illustrates another embodiment of a wearable device for strokedetection.

FIG. 5 shows that as a wearable device is moved so does the plane ofaction, causing the accelerometer to track the change of plane andaccordingly adjust the movement in three dimensions.

FIG. 6 shows measurement of azimuth, roll and pitch by an accelerometer.

FIG. 7 shows one embodiment of a data capture workflow involvingmovement data measurements (e.g., acceleration).

FIG. 8 shows one embodiment of a workflow for calculating tremormeasurements from captured acceleration data.

FIG. 9 shows a graphical representation of acceleration data analyzedusing an application on a computing device.

FIG. 10 shows a graphical representation of distance data analyzed usingan application on a computing device.

FIG. 11 shows a graphical representation of movement data analyzed usingan application on a computing device.

FIG. 12 illustrates one embodiment of a system for detecting symmetricallimb movement.

FIG. 13 illustrates one embodiment of a system for detectingasymmetrical limb movement.

FIG. 14 illustrates another embodiment of a system for detectingasymmetrical limb movement.

FIG. 15 illustrates another embodiment of a system for detectingsymmetrical limb movement.

FIG. 16 illustrates another embodiment of a system for detectingasymmetrical limb movement.

FIG. 17 illustrates another embodiment of a system for detectingasymmetrical limb movement.

FIG. 18 illustrates another embodiment of a system for detectingsymmetrical limb movement.

FIG. 19 illustrates another embodiment of a system for detectingasymmetrical limb movement.

FIG. 20 illustrates another embodiment of a system for detectingsymmetrical limb movement.

FIG. 21 illustrates another embodiment of a system for detectingasymmetrical limb movement.

FIG. 22 illustrates another embodiment of a system for detectingsymmetrical limb movement.

FIG. 23 illustrates another embodiment of a system for detectingasymmetrical limb movement.

FIG. 24 illustrates another embodiment of a system for detectingsymmetrical limb movement.

FIG. 25 illustrates another embodiment of a system for detectingasymmetrical limb movement.

FIG. 26 shows one embodiment of an application on a computing device forcomparing two sets of data from two limbs.

FIG. 27 shows a graphical representation of acceleration data from twowrists.

FIG. 28 shows a graphical representation of distance data from twowrists.

FIG. 29 shows a graphical representation of movement data from twowrists.

FIG. 30 shows a graphical representation of movement data from twowrists, while using a zoom feature of an application on a computingdevice.

FIG. 31 shows a graphical representation of distance data from twowrists.

FIG. 32 shows a graphical representation of acceleration data from twowrists.

FIG. 33 illustrates one embodiment of an architecture of a dataprocessing module.

FIG. 34 illustrates one embodiment of machine learning model used tomodel movement patterns of a person, for example while sleeping.

FIG. 35 illustrates another embodiment of machine learning model used tomodel movement patterns of a person.

FIG. 36 illustrates another embodiment of machine learning model used tomodel movement patterns of a person.

FIG. 37 illustrates an embodiment of a system for detecting stroke.

FIG. 38 illustrates an embodiment of a digital “FAST” test.

FIG. 39 illustrates an embodiment of a system for detecting stroke thatis configured to stimulate a response symmetrically and measure anoutput of the response to determine whether the response is symmetricalor asymmetrical.

FIG. 40 illustrates an embodiment of a wearable system for detecting ananomalous biologic event.

FIG. 41 illustrates another embodiment of a wearable system fordetecting an anomalous biologic event.

FIG. 42 illustrates a support structure coupled to the heat source ofone embodiment of a wearable system for detecting an anomalous biologicevent.

FIG. 43 illustrates a cross-sectional view of a wearable system fordetecting an anomalous biologic event.

FIG. 44 illustrates one embodiment of a tensionable band for coupling awearable system to a skin surface.

FIG. 45 illustrates a first and second wearable system for measuringresponse asymmetry across a right and left limit, respectively.

FIG. 46A illustrates in graph form a method of processing a signalreceived from a blood volume sensor.

FIG. 46B illustrates in graph form a method of monitoring a heatingcycle and a corresponding vasodilation response over time.

FIG. 47 illustrates in graph form a vasodilation response of a skinsurface over time and in response to application of heat.

FIG. 48 shows a method of detecting an anomalous biologic event bymeasuring a vasodilation response of a skin surface over time inresponse to application of heat.

FIG. 49 illustrates an embodiment of a thermal stimulator integratableinto a wearable system.

FIG. 50 illustrates another embodiment of a thermal stimulatorintegrated into a wearable system.

FIG. 51 illustrates an in-ear wearable system for measuring one or morebiometrics.

FIG. 52 illustrates a method of detecting an anomalous biologic event.

FIG. 53 illustrates a method of measuring heart rate variability of auser.

FIGS. 54-55 show graphs comprising electrocardiogram data for detectingan anomalous biologic event.

FIG. 56 shows a graph comprising asymmetrical electrodermal activitydata for detecting an anomalous biologic event.

FIG. 57 shows a graph comprising various parameters of interest inelectrodermal activity data.

FIG. 58 shows a method for measuring heart rate variability of a userand various feature analyses.

FIG. 59 shows a time domain analysis of heart rate variability data.

FIG. 60 shows a geometrical analysis of heart rate variability data.

FIG. 61 shows a frequency domain analysis of heart rate variabilitydata.

FIG. 62 shows a nonlinear analysis of heart rate variability data.

FIG. 63 shows a method of measuring a skin conductance response.

FIG. 64 shows a graph comprising asymmetrical skin conductance responseover time.

FIG. 65 shows a graph comprising amplitude of an asymmetrical skinconductance response over time.

The illustrated embodiments are merely examples and are not intended tolimit the disclosure. The schematics are drawn to illustrate featuresand concepts and are not necessarily drawn to scale.

DETAILED DESCRIPTION

The foregoing is a summary, and thus, necessarily limited in detail. Theabove-mentioned aspects, as well as other aspects, features, andadvantages of the present technology will now be described in connectionwith various embodiments. The inclusion of the following embodiments isnot intended to limit the disclosure to these embodiments, but rather toenable any person skilled in the art to make and use the contemplatedinvention(s). Other embodiments may be utilized, and modifications maybe made without departing from the spirit or scope of the subject matterpresented herein. Aspects of the disclosure, as described andillustrated herein, can be arranged, combined, modified, and designed ina variety of different formulations, all of which are explicitlycontemplated and form part of this disclosure.

Described herein are systems, devices, and methods for multivariatedetection of stroke. Multivariate may include using more than one, atleast two, or a plurality of factors, markers, or other parameters todetect stroke. In some embodiments, multivariate may include using oneparameter measured at multiple locations or positions or at multipletimes (e.g., random or fixed intervals, on demand, automatically, etc.).In various embodiments, multivariate may include detecting a measuredparameter symmetrically or asymmetrically. The measured parameter mayinclude a functional parameter (e.g., gait, speech, facial changes,etc.); a biological parameter or marker (e.g., blood proteins,metabolites, etc.); a quantitative parameter (e.g., limb asymmetry,heart rate variability, etc.); a spatial (e.g., neck vs. chest; arm vs.leg; etc.) difference in one or multiple (e.g., 2, 3, 4, 5, 10, 15, 20,etc.) measured parameters; and/or a temporal difference in one ormultiple measured parameters.

In some embodiments, there may be an overlay of multivariate signalsincluding two measurement data types, physiological or quantitativesignals (e.g., skin electromagnetic potential, Doppler flow signalanomaly, hyperhydrosis, cutaneous blood flow, brain perfusion, heartratevariability, etc.), and/or clinical manifestations or functionalparameters (e.g., limb asymmetry, speech slur, facial droop, retinalabnormality, etc.). Clinical manifestations occur following strokeonset, but a faint signal from a clinical manifestation measurementcombined with a physiological signal measurement may detect or predictstroke likelihood prior to stroke onset. Parameters that may be measuredbefore, during, or after a stroke include quantitative parameters,functional parameters, and/or blood/fluid parameters. Any of theparameters shown/described herein may be measured asymmetrically, asdescribed elsewhere herein. Exemplary, non-limiting examples ofquantitative parameters include: volumetric impedance spectroscopy, EEGasymmetry, brain perfusion, skin/body temperature (e.g., cold pareticlimit, up to 6° C. colder or 16% colder than non-paretic limb),hyperhidrosis (e.g., greater than 40-60% increase on paretic limb), limbasymmetry, drift and pronation test, cutaneous blood flow, muscle tone,heartrate variability (e.g., decrease in spectral components by greaterthan 10×, lasting 3-7 days after stroke onset), facial surface EMG,cerebral blood flow (CBF), carotid artery stenosis, salivary cortisol,neuron specific enolase (NSE), salivary (NSE), etc. Exemplary,non-limiting examples of functional parameters include: speech changes,speech comprehension, text comprehension, consciousness,coordination/directions, facial muscle weakness, arm weakness, bodyweakness (e.g., grip), leg weakness, foot weakness, unilateral weakness,difficulty walking, vertigo, sudden vision problems, limited visualfield, altered gaze, thunderclap headache, nuchal rigidity (nape ofneck), respiration, blood pressure (e.g., increase up to 60% in bothsystole (200 mHg) and diastole (140 mmHg)), etc. Exemplary, non-limitingexamples of blood/fluid parameters include: CoaguCheck (Roche),HemoChron (ITC), iSTAT (Abbott), Cornell University, ReST (Valtari BioInc.), SMARTChip (sarissa Biomedical), etc.

In some embodiments, multiple measurement locations (e.g., radial,brachial, etc. vessels) may be used to measure a difference in signal ordata pattern among those locations compared to nominal, healthy locationmeasurements or compared to an individual baseline as an input into adata processing module. For example, an individual baseline may berecorded over time and, when an adverse event occurs, a change (e.g.,absolute or relative value) from baseline is determined unilaterally orbilaterally. In some embodiments, after the adverse event occurs, a newbaseline may be established. Further for example, as shown in FIG. 2,blood pressure pulse varies depending on the location in the body,demonstrating that a slightly different signal is measured depending onlocation. For example, if only one location is measured, then changesover time are observed. If multiple locations are monitored and/ormeasured, then changes over time and changes relative to one anotherand/or a baseline can be used to identify a pattern or an asymmetricsignal occurrence. In some embodiments, an individualized baseline isfurther calculated based on a patient's health history (e.g., diabetes,heart-pacing, pre-existing stroke, menopause etc.), demographics,lifestyle (e.g., smoker, active exerciser, drinks alcohol, etc.), etc.

In some embodiments, as shown in FIGS. 1A-1B, a system 100 formultivariate detection of stroke includes a hardware component (e.g.,wearable device, sensor, computing device, remote sensing device, etc.)and a data processing module stored in the hardware or in communicationwith the hardware. The hardware component, for example one or moresensors, may be positioned on a user of the system, bilaterally on auser of the system, or throughout a location occupied by a user.Optionally (shown by dashed lines), a system for multivariate strokedetection may further include a third party device, for example a deviceincluding Amazon® Alexa® or an Amazon® Echo® device, as described infurther detail elsewhere herein. For example, there may be bidirectionalcommunication (e.g., via a wired connection or wireless communication)between the hardware component and the data processing module, the dataprocessing module and the third party device, and/or the third partydevice and the hardware component.

In one exemplary, non-limiting embodiment of the system of FIG. 1, adigital FAST (i.e., facial drooping, arm weakness, speech difficulties,time for help) test may be performed by the system of FIG. 1. Forexample, the hardware component may include one or more cameraspositioned throughout a location occupied by a user and configured todetect changes (e.g., using computer vision techniques) in facialexpressions (e.g., drooping) as a result of stroke, as shown in FIG. 38(i.e., the “F” part of a FAST test). Further, one or more sensors orother hardware component (e.g., camera, microphone, etc.) may bepositioned throughout the location occupied by user. The one or moresensors are communicatively coupled to the data processing module suchthat parameters sensed by the sensors may be transmitted to the dataprocessing module for digitization, filtering, process, and/or analysis.In the case of a digital FAST test, asymmetrical arm weakness may besensed by the one or more sensors. To discern speech difficulties, athird party device configured to receive and assess speech quality maybe communicatively coupled to the data processing module and/or hardwarecomponent. As such, a user may be prompted to speak by the third partydevice and the user's response may be sensed by the hardware component(e.g., one or more microphones) so that a quality of speech of the usermay be determined. One or more of these detected parameters may beanalyzed and optionally sent to a caregiver, approved family and/orfriends, healthcare provider, physician, and/or emergency services.

In some embodiments, a system for multivariate stroke detection mayfurther include an application downloaded and/or stored on a hardwarecomponent or downloaded and/or stored on a computing device (e.g.,mobile computing device) communicatively coupled to the hardwarecomponent. The application may be configured to process sensor data,camera data, speech data, etc. and/or display data sensed or captured inreal time, for example in a graphical representation, and/or allowzooming to view various features of the data.

In some embodiments, data may be transmitted to and/or from the devicefor detecting stroke to a central hub, mobile computing device, server,or other storage and/or computing device. Data transmission may includewireless communication (e.g., a nearfield communications (NFC) protocol,a low energy Bluetooth® protocol, other radiofrequency (RF)communication protocol, etc.) between sensor locations on the bodyand/or a central hub. In other embodiments, data transmission mayinclude wire communication between sensor locations on the body and/or acentral hub. In some embodiments, the central hub may be a monitor in amedical facility, home monitor, patients' mobile computing device, orother wireless device. Alternatively, one or more of the sensors on thebody may act as the central hub. The hub device may wirelessly sendsignals to activate a medical care pathway and/or notify one or moreindividuals (e.g., family, friends, physician, EMS, etc.).

In some embodiments, data transmission, following multivariate analysis,to the central hub may alert the patient, the next of kin, and/or athird party to identify possible false positives or negatives.

In some embodiments, a device for stroke detection may be worn on anexterior or skin surface of the patient or implanted as hardware priorto and/or during stroke, including up to days before the event andduring the event to provide continuous variable monitoring of variousphysiological parameters. The various embodiments described herein mayeither be a wearable device or an implantable device.

In some embodiments, a device for detecting stroke may include awearable device, for example a patch, headband or sweatband, ring, watch(e.g., to measure movement as shown in FIG. 7), adhesive strip, helmet,bracelet, anklet, sock (e.g., to measure heart rate, heart ratevariability, temperature, gait, etc.), shoe insoles (e.g., to measureheart rate, heart rate variability, temperature, gait, etc.), clothing,belt, necklace, earring (e.g., over or in the ear to measure heart rate,heart rate variability, EEG asymmetry, etc.), hearing aid, earbuds,glasses or sunglasses or smart glasses (e.g., to measure EOG, EMG, EEG,gaze, facial muscle movement or drooping, etc.), smart tattoo (e.g., tomeasure EEG, ECG, etc.), bra, bra clip, chest strap, contacts (e.g., tomeasure tear composition, etc.), mouthguard or bite splint (e.g., tomeasure saliva neuron specific enolase, cortisol, temperature, motion,etc.), hat or cap (e.g., to measure various signals using ultrasound),wearable speaker (e.g., to measure heart rate, heart rate variability,motion, etc.), or otherwise a sensor integrated into any wearableclothing, accessory, or device. For example, a patch (e.g., wearable onthe neck) may be used to estimate cerebral blood flow using dopplerultrasound, blood oxygen content, or other blood feature as an indicatorof blood going into the brain (Carotid Artery) or leaving the brain(Jugular Vein); a patch or strip (e.g., wearable on the head) may beused to detect EEG or sEMG. Further for example, a wearable device fordetecting stroke may include one or more transdermal sensors that areconfigured to measure changes in one or more gasses transfused throughthe skin (e.g., Nitric Oxide (NO) could either be measured directly, orthrough measurement of particular bi-products); one or more biomarkersthat are in the blood that are diffused into the subcutaneous region orinto the epidermis and can be measured externally. In some embodiments,a wearable device for detecting stroke may comprise a wristband or patchwith a combination of micro-needles that are configured to measure thefluid sub-dermally or interstitial fluid (e.g., similar to continuousglucose monitors).

In some embodiments, a wearable device for detecting stroke may comprisea wearable array of indicators (e.g., chromogenic indicators) configuredto measure a chemical, analyte, protein, etc. in a bodily fluid of anindividual (e.g., blood, interstitial fluid, etc.). For example, thearray may comprise a membrane with a printed array thereon that whenexposed to one or more analytes, a subset of the indicator spotsresponds by changing color or properties. The color response of theindicators may be optically read, for example using a camera on acomputing device or other image sensor and compared to a baselinereading or a reference or standard. A color difference map may begenerated by superimposing and/or subtracting the two images (baselineand experimental or experimental and reference/standard). As anexemplary, non-limiting analyte, an increase in nitric oxide may bedetected in blood or interstitial fluid of an individual after a strokeevent and/or modification of one or more proteins by nitric oxide may bedetected in blood or interstitial fluid of an individual after a strokeevent and/or one or more intermediates or byproducts of nitric oxide maybe detected in blood or interstitial fluid of an individual after astroke event. For example, nitric oxide has been shown to modifyproteins via: 1) binding to metal centers; 2) nitrosylation of thiol andamine groups; 3) nitration of tyrosine, tryptophan, amine, carboxylicacid, and phenylalanine groups; and 4) oxidation of thiols (bothcysteine and methionine residues) and tyrosine. Such methods may bypassthe need to measure an asymmetrical change in one or more parameters, asdescribed elsewhere herein.

In some embodiments, a system for stroke detection may include one ormore Doppler radar sensors, microphones, and cameras throughout a hometo detect visual signs of stroke, equivalent to a “FAST” test usingcomputer vision or similar techniques, as shown in FIG. 38. For example,a machine learning model may be trained on a training data set of imagesof stroke patients to identify asymmetrical facial features, such asfacial drooping. As can be seen in FIG. 38, the system is able toidentify drooping in a mouth, nose, and eye positioning of the patient.Facial capillary asymmetries via high frame-rate Eulerian videoprocessing techniques may also be detected by the systems describedherein. The system may further employ confirmation biometrics such asHR/HRV, respiratory rate (e.g., via Doppler radar), and/or bilateraltemperature via infrared camera (i.e., FLIR)

In some embodiments, a device for detecting stroke may include a devicepositionable in a room, office, home, vehicle, or other location; or inor on a bed or other furniture (e.g., bedside monitors; monitors withinmattresses, bedding, etc.). For example, a smart speaker (e.g., toprompt a user to respond to a question to analyze speech quality),microphone, camera, and/or mirror may be positionable in a location todetect changes in a user's speech, activities, movement, gait, facialappearance, heart rate, and/or heart rate variability. The device maycomprise a data processing module to differentiate changes in themeasured parameters as compared to that from healthy learned patientdata or individualized baseline data. This can be also be referred to asreference data. The healthy learned patient data may be unique to aparticular user or an aggregate value that is predetermined fromprevious studies. The healthy learned patient data or individualizedpatient data can be stored as a one or more parameters or a signature.

In some embodiments, as shown in FIG. 3, the device may be a ring or apair of rings to be worn one on each hand or each foot to measuretemperature; volumetric impedance spectroscopy; hyperhidrosis; heartrate or heart rate variability through, for example, a PPG sensor tomonitor rate of blood flow; and/or motion (e.g., by including anaccelerometer and/or gyroscope therein) to measure, for example, limbasymmetry or changes in gait. Temperature measurement devices mayinclude, but are not limited to, infrared sensors, thermometers,thermistors, or thermal flux transducer. Hyperhydrosis measurementdevices may include, but are not limited to, detection of analytesincluding ions, metabolites, acids, hormones, and small proteins throughpotentiometry, chronoamperometry, cyclic voltammetry, square wavestripping voltammetry, or detection of changes in conductivity. Sensormeasurement devices may include, but are not limited to, aphotoplethysmographic (PPG) device, a skin conductance sensor measuringskin conductance/galvanic skin response (GSR) or electrodermal activity(EDA), or a skin temperature measurement device (e.g., contact devicesand non-contact devices, like IR imaging camera).

In some embodiments, the ring may incorporate a stretchable orexpandable element or stretch sensor to allow the ring to expand orstretch when the finger swells. This element may include, but is notlimited to, elastomer film polymers of various degree of bonding toallow for different pliable elements or measuring the reflectivity ofpolarized light. This element may comprise a plastic segment of the ringthat can be loosened/tightened, or by building a slidable element thatcan be pulled apart. Non-limiting examples of a stretch sensor include,but are not limited to, a strain gauge or an electrical componentconfigured to change inductance, resistance, or capacitance whenstretched.

In some embodiments, the device may be a strip that measures brain wavesthrough electroencephalogram (EEG) and/or muscle contractions throughsurface electromyography (sEMG). The measurement of EEG may be comparedto a baseline value to detect a change or asymmetry of the EEG. In someembodiments, EMG measures facial muscle changes compared to a baselinemeasurement to identify muscle weakness and tone.

In some embodiments, as shown in FIG. 4, the device may be a wearableeyeglass device that measures electrooculography (EOG), EMG, EEG, gaze,and facial muscle symmetry. The measurement of EOG identifies a changein the corneo-retinal standing potential between the front and back ofthe eye that may detect a change in gaze and size of visual field andmay be compared to either the other eye or a previous baseline value.

In some embodiments, as shown in FIGS. 5-6, a device for strokedetection may include a wearable device for measuring changes in motion(e.g., in three axes), for example asymmetrical motion to detecttremors. In some embodiments, a device for stroke detection may includea wearable device for measuring changes in motion (e.g., in three axes),for example asymmetrical changes in motion to detect tremors. Suchdevice may include an accelerometer, gyroscope, inclinometer, compass,or other device for measuring acceleration, distance, and/or movement.For example, as shown in FIG. 5, as the wearable device is moved so doesa plane of action. The accelerometer may track a change of plane andaccordingly adjust the movement in three dimensions. Further, as shownin FIG. 6, an accelerometer may track azimuth, roll and pitch.

In some embodiments, a device for detecting stroke may be configured todetect asymmetrical responses, outputs, or signals. For example, one ormore devices (e.g., ring, watch, etc.) described herein may be used tomeasure symmetrical and asymmetrical limb movement. FIGS. 12-25 showvarious symmetrical and asymmetrical movements that may be measured byone or more embodiments described herein. For example, FIGS. 12, 15, 18,20, 22, and 24 show various embodiments of symmetrical movements (e.g.,up and down movement, left and right movement, rotational movement,etc.) between two limbs measurable by various devices described herein.FIGS. 13-14, 16-17, 19, 21, 23, and 25 show various embodiments ofasymmetrical movements (e.g., up and down movement, left and rightmovement, rotational movement, etc.) of limbs measurable by variousdevices described herein.

In some embodiments, as shown in FIG. 39, a device or system fordetecting stroke may be configured to stimulate a response and measurethe response on each side (e.g., to detect asymmetrical responses) ofthe body of the user to determine whether the response or the differencein response between the two sides indicates a stroke event. For example,a thermal (i.e., hot or cold) stimulus may be applied to a section ofskin on a body of a user (shown in top panel) and the body's response tothe thermal stimulus may be monitored over time (shown in bottom panel)to determine whether homeostasis is reached and/or a difference inresponse or return rate exists between the two sides of the body (inother words, determine whether an asymmetrical response exists). Furtherexamples include stimulating the muscular or nervous system usingelectrical signals and monitoring the response over time and/or betweensides using electromyogram (EMG), bioimpedance, or electroneurogram(ENG), respectively. These “stimulators/transmitters” and“receivers/detectors” could be in the same region or could be separatedto measure across regions of the body.

As discussed above, if a stroke is detected and patients seek carequickly, it can dramatically reduce death and disability. Continuousmonitoring for a stroke event may improve the response time. However,continuous monitoring of anomalous biologic events such as stroke eventsusing existing monitors can be challenging. These monitors arecumbersome and may be difficult for users to wear over an extendedperiod of time. In contrast, the inventors realized that wearabledevices, such as watches with integrated sensors and electronics mayimprove continuous monitoring of stroke events. An impaired vasodilationresponse may be indicative of a stroke, heart failure, hypertension,diabetes, menopause, or other conditions.

Applying heat stress to a portion of the skin may enable detection ofvasodilation response. Accordingly, systems and methods described belowenable detection of impaired vasodilation in a form factor that improvescontinuous anomalous cardiac event monitoring. In some embodiments, asshown in FIG. 40, a system or device 400 for detecting an anomalousbiologic event may function to heat a skin surface and measure avasodilation response of the skin surface. The system or device 400 mayfurther function to measure one or more additional parameters, biologicsignals, etc. as will be described in greater detail elsewhere herein.

In one example, a system or device 400 for detecting an anomalousbiologic event may include a body 416 having a first surface 404opposite a second surface 404 in contact with a skin surface of aperson. The first 404 and second 404 surfaces may be coupled via one ormore or a plurality of sidewalls 405. For example, one or more sidewalls405 may extend from a perimeter of the first surface 404 and couple to aperimeter of the second surface 402. The first 404 and/or second 402surface may include one or more sensors positioned thereon. For example,one or more sensors on the first surface 404 may measure an environmentof the user wearing or using the wearable system, and one or moresensors on the second surface 402 may measure one or more properties,features, or characteristics of the skin surface of the user and thusthe user itself. Alternatively, the first surface 404 may include one ormore sensors or imagers or cameras for assessing a facial region of auser, for example, via a FAST test.

A wearable device 400 may be secured to a user, for example a limb of auser or a skin surface of a user, via a coupling element 408, forexample a tensionable band, which will be described in greater detailelsewhere herein. The coupling element 408 may be adjustable such thatthe wearable device may be cinched or tensioned to promote greatercontact and thus coupling between the wearable device and the skinsurface or tension released to reduce contact or coupling between thewearable device and the skin surface. As shown in FIG. 41, a couplingelement 408 may be coupled to a body 416 of a wearable device via one ormore connectors 422 a, 422 b, 422 c, 422 d. For example, a couplingelement 408 may couple to a body 416 of a wearable device via aconnector 422 that includes one or more pin joints, a snap fitconnection to the coupling element 408, a slide and fit connection tothe coupling element 408, etc. When the tensionable band 408 is coupledto the body 416 via connectors 422, the tensionable band is centeredwith respect to one or more sensors positioned on the second surface, sothat there is sufficient coupling between the sensors and the skinsurface.

A wearable device 400 may include a heat source 410 in communicationwith the skin surface. The heat source 410 is configured to heat theskin surface to a target temperature or a pre-determined temperature.The heat source 410 may be a heating element; an environmental heatsource, for example a warm room, warm environment (e.g., under thecovers, hot day, etc.); thin film resistance flexible heater; polyimideheater; etc. In some embodiments, a heat source 410 is positioned on asecond surface 402 of the body 416, so that there is coupling or contactbetween the heat source 410 and a skin surface. Alternatively, a heatsource 610 or one or more sensors 612, 626 may be positioned on acoupling element 608 of the system 600, as shown in FIG. 50, such thatthe body 616 is separate from the sensor module 609 that includes theheat source 610 and the one or more sensors 612, 626. Alternatively, theheat source and/or one or more sensors may be distributed between thecoupling element, body, and sensor module depending on which sensors areincorporated into the system and their specific requirements orparameters.

In some embodiments, as shown in FIG. 49, a heat source 710 may comprisea thermal stimulator comprising a single printed layer of resistive inkon polyimide film 702. Heat traces 704 and traces to one or more sensors706 (e.g., blood volume sensor, infrared sensor, temperature sensor,etc.) could also be likewise printed on the polyimide film 702, as shownin FIG. 49.

In a still further embodiment, the sensor module 809 may be positionablein an in-ear device (e.g., ear lobe clip, ear bud, hearing aid, etc.),as shown in FIG. 51. The sensor module may be configured to measure oneor more parameters, depending on which sensors are present, for exampleblood pressure, temperature, and/or oxygen saturation.

Further, the heat source 410 may be communicatively coupled to ahardware processor such that the hardware processor outputs a heatingsignal to the heat source 410 to activate the heat source to initiate aheating cycle. For example, a heating cycle may include receivingbaseline temperature signals from a skin temperature sensor and anenvironmental temperature sensor, determining the target temperaturebased on the baseline temperature signals, and determining whether thetarget temperature is below a maximum temperature value.

In some embodiments, a target temperature may be equal to a baselineskin temperature as measured by the skin temperature sensor plus about 1to about 20 degrees, for example about 1 to about 5 degrees, about 1 toabout 10 degrees, about 5 to about 10 degrees, about 5 to about 15degrees, about 8 to about 12 degrees, etc. In one embodiment, the targettemperature is equal to the baseline skin temperature as measured by theskin temperature sensor plus about 5 to about 15 degrees. In anotherembodiment, the target temperature is equal to the baseline skintemperature as measured by the skin temperature sensor plus about 7 toabout 13 degrees. In another embodiment, the target temperature is equalto the baseline skin temperature as measured by the skin temperaturesensor plus about 10 degrees. If the target temperature is greater thana maximum temperature value, the system pauses or delays until thebaseline skin temperature drops below a minimum threshold orrecalculates the target temperature so that it is less than the maximumtemperature value. If the target temperature is less than a maximumtemperature sensor, the system proceeds to activate the heat source toheat the skin surface to the target temperature.

In some embodiments, the heat source cycles between the targettemperature and a deactivated or off state or between the targettemperature and a temperature that is lower than the target temperaturebut greater than the skin baseline temperature, for example to maintainthe target temperature, hereinafter referred to as a dwell time.

In some embodiments, a duration of a heating cycle and a targettemperature are interconnected and based on user preference or userperception of heat on the skin surface or a vasodilation response of theuser. For example, a higher target temperature may be used for a shortertime period or a lower target temperature may be used for a longer timeperiod.

Further, the system or device 400 may be configured to receive one ormore user inputs related to a perceived heat sensation on the skinsurface and/or to a sensitivity of a vasodilation response of the user.For example, a user may input that the target temperature felt too hotor too cold, for example via a user input element (e.g., button), suchthat the system responds by reducing the target temperature butelongating an amount of time that the skin is heated. Additionally, oralternatively, based on user preference, preset configurations (e.g.,during manufacturing), or as a result of sensed data (e.g., based onsensor data), the heat source may reach the target temperature via oneof a plurality of ramping functions, for example slow ramping, largerstep functions, etc. Alternatively, the heat source may reach the targettemperature through a plurality of micro-stimulations. Further, forexample, a target temperature may be individualized for the user basedon the sensitivity of the vasodilation response of the user.

In some embodiments, a device or system 400 for detecting an anomalousbiologic event includes a support structure 428 coupled to the heatsource 410 and configured to couple the heat source 410 to the secondsurface 402. For example, as shown in FIG. 42, the support structure 428includes arm 432 that extends towards or to a center of the heat source410 to support the heat source 410 and one or more spokes 430 thatextend from the arm 432 to a perimeter of the heat source 410. Thespokes 430 may be substantially equally spaced from adjacent spokes 430.The spokes 430 may also be circumferentially arranged about pin or joint434. Spokes 430 of support structure 428 further define air flowapertures 442 to allow air to interact with the heat source 410 to coolthe heat source 410. Spokes 430 further define air flow apertures 422 toat least partially expose the heat source to a cavity defined by thefirst and second surfaces as described elsewhere herein. Alternatively,or additionally, heat source 410 may be cooled by one or more vents, ablower for passing airflow over the heat source 410, coolant, or anothermechanism known to one of skill in the art.

In some embodiments, support structure 428 exerts pressure on the heatsource 410 to increase contact or coupling between the heat source 410and the skin surface. In one embodiment, the tensionable band includes astrain gauge that determines the tensile stress the band is subjectedto. The strain gauge output or signal could then be visualized ordisplayed to a user so the user knows if the band is tensioned to anappropriate level for the heat source and/or sensor(s). Alternatively, aspring constant (k) of the material may be used to calculate the force(F=kx), so depending on how much the material is stretched (put intension), the band could indicate that force based on the displacement.As such, the support structure 428 may comprise a flexible material, forexample a flexible plastic. In other embodiments, the support structure428 comprises a rigid material.

Further, as shown in FIGS. 40-41, a device or system 400 for detectionof an anomalous biologic event further includes a skin temperaturesensor 414 and a blood volume sensor 412. The blood volume sensor 412can be integrated into a form factor such as the device or system 400that improves continuous anomalous cardiac event monitoring. The bloodvolume sensor 412 can measure parameters that can provide vasodilationresponse. Furthermore, the skin temperature sensor 414 can also beintegrated into the device or system 400. The skin temperature sensor414 is positioned on the second surface 402 and configured to measure atemperature of the skin surface in contact with the heat source 410. Theblood volume sensor 412 is positioned on the second surface 402 andconfigured to measure a blood volume of the skin surface. The bloodvolume sensor may be a photoplethysmography sensor or an impedanceplethysmographic sensor. The blood volume sensor may employ light at 530nm (green), 645 nm (red), 470 nm (blue) wavelength, or a combinationthereof. Different wavelengths may be more appropriate for differentapplications, for example green (530 nm) light may be more accurate forheart rate measurements (e.g., heart rate variability, heart rate,etc.). In addition to, or alternatively, the blood volume sensor may befurther configured to measure one or more of: heart rate, heart ratevariability, or oxygen saturation.

A system or device 400 for detection of an anomalous biologic event mayinclude an environmental temperature sensor configured to measure atemperature of the environment around the wearable system 400. Forexample, the environmental temperature sensor may be positioned on thefirst side 404 of the body 416 of the wearable system, opposite thesecond side 402 that includes the heat source 410. Alternatively, thesystem or device 400 may be communicatively coupled to an environmentaltemperature sensor on or in a remote computing device. For example, theremote computing device may include a laptop, a cellular device, aworkstation, a server, a desktop computer, a personal digital assistant,a second wearable system or device, a netbook, or the like.

The skin temperature sensor and/or environmental temperature sensor mayinclude a thermocouple, a resistance temperature detector, a thermistor,or an infrared temperature sensor. The type of temperature sensorselected may depend on error rate, coupling to skin surface efficiency,among other features.

In some embodiments, the heat source 410 is positioned concentricallyabout one or both of the blood volume sensor 412 and the skintemperature sensor 414, as shown in FIGS. 40-41. Although, a location orposition of the blood volume sensor 412 and the skin temperature sensor414 that enables coupling to a skin surface is envisioned.

A hardware processor (within the wearable system or communicativelycoupled to the wearable system) communicatively coupled to the skintemperature sensor 414 and the environmental temperature sensor may beconfigured to perform a method comprising: receiving a first temperaturesignal using the skin temperature sensor and a second temperature signalusing the environmental temperature sensor; and calculating atemperature differential between the skin temperature and theenvironment temperature. For example, if the temperature differential isbelow a set threshold, a difference between the target temperature andthe maximum temperature value may be increased. In contrast, if thetemperature differential is above a set threshold, a difference betweenthe target temperature and the maximum temperature value may be reduced.The environmental temperature sensor may also be used in analysis ofdetermining erroneous results, such as false positive indications ofabnormalities. By comparing signals before and after stimulus and/or bycomparing left versus right limit, externalities such ambienttemperature response may be reduced in the analysis of abnormalities.

Further, the hardware processor may be coupled to the heat source 410and the blood volume sensor 412. In some instances, the system 400describe above can enable non-invasive monitoring of vasodilation and/orvasoconstriction. Human body regulates stable equilibrium through theprocess of homeostasis. For example, if a stimulus is applied to a bodyof patient, one or more homeostatic processes will attempt to counteractthe effect of stimulus. For example, with respect to an induced thermalstimulus that increases or decreases temperature at a tissue site, thebody will attempt to reverse the temperature change through blood flow(vasodilation or vasocontraction). Accordingly, the system 400 caninduce and measure the vasodilatory response. As discussed above, strokeand other abnormalities can impair the vasodilatory response. Therefore,in some instances, it may be advantageous to monitor the change in thevasodilatory response to determine abnormalities, such as stroke. Ablood volume sensor, such as optical sensors, can enable monitoring ofthe blood flow and correspondingly the vasodilatory response. In someinstances, one or more temperature sensors (through a thermistor oroptical radiation-based detectors) can also enable determination of thevasodilatory response by monitoring how quickly the temperature of theskin returns to equilibrium following the stimulus. In some examples,the vasodilatory response is correlated with a rate of change or slopein the measured parameter, such as blood volume parameters, temperature,and others discussed herein. In additional examples, the vasodilatoryresponse can be correlated with a steepness of the rate of change. Thiscan be calculated using a second derivative.

In some instances, it can be advantageous to use a combination of a heatsource 410 and the blood volume sensor 412 to improve cardiacmonitoring. The heat source 410 and the blood volume sensors 412 can beintegrated into a form factor that a user can wear for continuousmonitoring. The measurements can be repeated non-invasively withoutsignificant discomfort to the patients. Furthermore, as shown in FIGS.46A-B and 47, the response time between the application of heat and thechange in blood volume is relatively small. This can enable a relativelyfast determination of the anomalous biologic event. Therefore, it can beadvantageous to integrate a heat source and a blood volume sensor in anywearable system disclosed herein to improve continuous cardiacmonitoring. In some instances, a Peltier cooler can be used as a thermalsource instead of or in addition to the heat source 410.

Furthermore, in some instances, the stimulus can be an electricalstimulus in addition to or instead of the thermal stimulus. For example,the system 400 may include a plurality of electrodes for inducing and/ormeasuring electrical activity across a tissue site. Electrical activitycan include bioimpedance for detecting high or low muscle tone, whichcan occur with hemiplegia. The system 400 can include at least twoelectrodes. In some instances, the system 400 can include at least fourelectrodes. For example, the system 400 can include two pairs ofelectrodes for measurement of bioimpedance. These four electrodes maypositioned on the second surface 402. The electrodes may also bepositioned on the strap 408 or an external accessory that can attach thesystem 400. Bioimpedance can measure muscles both inter and transcellularly which could be used to detect hemiparesis and could be usedfor both detection as well as rehabilitation. The EDA electrodes canalso be mounted anywhere along the second surface facing the skin to thestrap 408. Furthermore, the system 400 can also include six or moreelectrodes. The electrodes can be integrated on the system 400 such thatthey are in contact with the skin tissue of the user.

As discussed above, an optical sensors, such as the blood volume sensor412, can interrogate a target tissue to determine parameters thatcorrelate with the vasodilatory response. Other sensors can also be usedto extract parameters for determination of the vasodilatory response.For example, the system 400 can use minimally invasive and/or invasivesensors to determine hemodynamic parameters, such as cardiac output, toprovide an indication of the vasodilation response. The system 400 canalso include on or more electrical based sensors, such as bioimpedancesensors, EDA sensors, ECG sensors, EEG sensors, EMG sensors, and thelike. Electrical sensors may enable measurement of hydration, skinconductance, bioimpedance, and other electrical parameters that relateto hemodynamic function or measure electrical signaling of neuralactivity and its effect. Furthermore, the system 400 can include one ormore ultrasound sensors to obtain hemodynamic parameters. Temperaturesensors can also enable determination of the vasodilation response.Accordingly, the system 400 can include a combination of some or all ofthe sensors discussed above to extract one or more parameters thatcorrelate with hemodynamic function or maintenance of homeostasis.

The following table illustrates example physiological phenomena andcorresponding parameters that can be monitored:

Physiological Phenomena Data Output Bilateral electrodermal activity(EDA) Skin conductance response Autonomic regulation of vasomotor Bloodflow amplitude, systole and response to maintain homeostasis diastoleinterval, transient vasodilation and vasoconstriction Temperature decaypattern upon Transient temperature versus thermal stimuli time outputOxygen saturation IR absorption oxygenated hemoglobin to deoxygenatedhemoglobin Motion asymmetry Actigraphy Bilateral temperature differenceSkin temperature Ambient conditions Ambient temperature Changes inmuscle tone (hemiparesis) Bio impedance (BIA) and hydration (hydrosols)

Patients are often monitored in neuro ICU after a stroke. This can beexpensive as a nurse needs to conduct periodic checks on the patient.Accordingly, the system 400 can enable improved monitoring withoutrequiring the patient to be in the neuro ICU and/or without requiring acaregiver to conduct periodic checks. While the system 400 is describedas a wearable system, in some examples, some or all of the components ofthe system 400 may be positioned in proximity to the user but notdirectly attached or worn by the user. For example, when a user needs tobe monitored in a hospital environment, some or all of the components ofthe system 400 can be positioned in proximity to the user's hospitalbed. For example, the thermal stimulus source can include a laser.

As such, the hardware processor may be configured to perform the method,as shown in FIG. 52, which includes: receiving a baseline blood volumesignal from the blood volume sensor S5202, outputting a heating signalto the heat source to initiate a heating cycle S5204, receiving a secondblood volume signal from the blood volume sensor S5206, comparing thesecond blood volume signal to the baseline blood volume signal S5208,and determining whether an anomalous biologic event has occurred basedon the comparison S5210. The steps of the method may be repeated atleast once, one or more times, a plurality of times, on a loop,according to physician, caregiver, or user preferences, or otherwise.

In some embodiments, the second blood volume signal is a set of bloodvolume signals, such that the blood volume of the skin surface ismeasured repeatedly before, during, and/or after a heating cycle of theheat source. The blood volume of the skin surface may be measured at apre-set interval, for example every about 10 ms to about 1 sec, about 1sec to about 5 sec, about 5 sec to about 10 sec, etc. Alternatively, theblood volume of the skin surface is measured randomly or only upondetection of a change in temperature of the skin surface or upondetection of a change in vasodilation by the blood volume sensor. Ameasurement frequency may be individualized for a user, for example if avasodilation response of a user in response to heat is very sensitive, areduced frequency of blood volume measurements may be needed. Incontrast, if a vasodilation response of a user in response to heat isless sensitive, an increased frequency of blood volume measurements maybe needed.

In some embodiments, the second blood volume signal is a plurality ofblood volume signals, such that the blood volume of the skin surface ismeasured continuously before, during, and/or after a heating cycle ofthe heat source.

In some embodiments, block S5206 includes receiving the second bloodvolume signal after the target temperature is reached, after apredetermined length of time has expired, after a dwell time (i.e.,cycling heat source on and off during a heat cycle or cycling heatsource between target temperature and lower temperature during a heatcycle) has expired, or after one or more heating cycles have concluded.A frequency of sampling and/or sampling relative to a heat cycle(before, during, or after the heat cycle) may be based on a user'sbiology, such that the sampling is individualized.

In some embodiments, block S5208 includes calculating a baseline ratioof alternating current (AC) to direct current (DC) for the baselineblood volume signal and a second ratio of AC to DC for the second bloodvolume signal and comparing the baseline ratio to the second ratio, asshown in FIG. 46A. The methodology and rationale for the AC to DC ratiois described in Tusman et al. “Advanced uses of pulse oximetry formonitoring mechanically ventilated patients.” Anesth Analg 2017; 124:62-71, which is herein incorporated by reference in its entirety. Thetop left panel of FIG. 46A shows raw PPG amplitude data and therespective DC and AC components of the signal. Taking the ratio of AC toDC of the raw signal yields the top right panel. During a two-heatingcycle experiment, PPG data in the lower left panel was collected. The ACand DC components of the signal are represented in separate, stackedgraphs. When the AC to DC ratio is calculated for this two-heating cycleexperiment, a normalized PPG signal is achieved, which is shown in thelower right panel. The same PPG data is shown in FIG. 46B overlaid withheat cycle data. As shown, the temperature of the skin surface reachesthe target temperature (i.e., about 42 C) in each heat cycle, shown bythe shaded portions of the graph. The perfusion index or normalized PPGsignal similarly spikes during each heat cycle in response to theapplication of heat. FIG. 47 shows the same data as FIGS. 46A-46B withadditional definition of baseline, vasodilation, and post vasodilationwindows. The heat cycle was off for 5 min, on for 5 min, off for 15 min,on for 5 min, and off for 10 min. The time windows selected forcomparison were: a baseline time window (e.g., minimum 2 minutes before“heat source first on”), a vasodilation time window (e.g., maximum 2minutes of “heat source on”), a first post vasodilation time window(e.g., minimum 2 minutes after “heat source first on”), and a secondpost vasodilation (e.g., minimum 2 minutes after “heat source secondon”). As shown in FIGS. 46A-47, application of heat elicits avasodilation response that is reproducible over multiple cycles.

As discussed above, tracking a vasodilation response can be used inmonitoring abnormalities, such as stroke. However, the vasodilationresponse in a user can be affected by several sources that are unrelatedto the stroke or the abnormality that is being monitored. Accordingly,using the system 400 in only one tissue site may result in falsepositives. It was observed by the inventors that by monitoring multipletissue sites, the monitoring results may more closely track theabnormalities and reduce erroneous results. FIG. 45 illustrates a firstsystem 400 and a second system 500 placed approximately symmetrically onthe right and left limbs. Accordingly, if a stimulus is appliedapproximately in synchronization between the first system 400 and thesecond system 500, the degree of symmetry or asymmetry in themeasurements responsive to the approximately simultaneous stimulationcan be used in the determination of stroke and reduction of erroneousresults. While the disclosure herein provides stroke as an example ofabnormalities, the system 400 and the methods described herein can alsobe used to monitor other abnormalities. For instance, otherabnormalities or physiological deviation can include menopause,diabetes, and peripheral blood circulation disorders that can affectperipheral blood circulation. In some instances, menopause, diabetes,and other disorders may affect all parts of the body or may affectcertain parameters uniformly. For example, vasodilation response may beimpaired uniformly in conditions like menopause compared to a strokewhere there is a high likelihood of asymmetry. Accordingly, a stroke canbe differentiated from these other abnormalities and vice versa based onthe asymmetry observed in the vasodilation response and othermultilateral measurements. In another example, the vasodilation responsemay be affected, but the electrical measurements described herein usingEDA and bioimpedance may remain the same. Accordingly, the asymmetry inmeasurements may also be used to determine abnormalities.

In some embodiments, as shown in FIG. 48, a method 4800 of detecting ananomalous biologic event includes: applying a high temperature stimulus(e.g., shown in FIGS. 46B-47) S4810; receiving one or more signalsindicative of a blood volume, blood flow, or blood perfusion in a tissueof the user in response to the high temperature stimulus S4820;extracting one or more features of the one or more signals S4830;comparing the one or more features for a right side and a left side ofthe user (e.g., right and left limbs, as shown in FIG. 45) S4840; andcalculating an acute stroke classification score S4850. Furthermore, themethod 4800 can optionally compare baseline measurements prior to theapplication of the stimulus and after the application of stimulus, asdiscussed in more detail with respect to FIG. 52 for both left and rightlimbs. During multiple tissue site monitoring, such as the left andright limb monitoring as shown in FIG. 45, the system 500 may includeall the same components as the system 400 described above. In othercases, the system 500 may include less components than system 400. Forexample, both systems may not require a display. Additionally, one ofthe systems may include computational capabilities while the other onecollects the data and transmits to the paired system for computation.Therefore, one of the systems 400 and 500 may not include a hardwareprocessor. Accordingly, the system 400 and 500 may operate in amaster-slave configuration. The systems 400 and 500 may be pairedwirelessly via Bluetooth or other wireless protocol. In some instances,the systems 400 and 500 may be paired with an external computing system,such a patient monitor, a hub, or a smartphone.

In some embodiments of block S4830, the one or more features include,but are not limited to, an amplitude or a systolic or diastolic wave, awaveform shape, a waveform complexity, a perfusion index (i.e., arelationship between the pulsatile (AC) and the non-pulsatile (DC)components of PPG signal), DC offset, a stiffness index (i.e., timebetween peaks of forward and backward waves along the vascular tree;h/ΔT, where h is a patient's height), a reflection index (i.e., a ratiobetween the heights of the backward and the forward waves; B/A×100), anotch position (i.e., position of the dichrotic notch; e.g., withvasoconstriction, the position moves toward the left into the systolicwave), a peak to peak phase shift, slope onset of temperature signaland/or blood volume signal, slope decay of temperature signal and/orblood volume signal, midpoint of rising slop of temperature signaland/or blood volume signal, a vasodilation response as an indicator of acollateral state of the brain and/or heart, etc.

In any of the embodiments described herein, a wearable system or devicefor detecting anomalous biologic events may include one or moreelectrodermal activity sensors positioned on the second surface and/or atensionable band of the system. For example, as shown in FIG. 41,electrodermal sensors 424, 426 are positioned on the second surface 402of the wearable system 400. Electrodermal sensors 424, 426 may be spacedapart from one another by distance 444, which equals about 5 mm to about10 mm, about 10 mm to about 20 mm, about 20 mm to about 30 mm, about 30mm to about 40 mm, about 40 mm to about 50 mm, about 50 mm to about 60mm, about 60 mm to about 70 mm, about 70 mm to about 80 mm, about 80 mmto about 90 mm, about 90 mm to about 100 mm, measured from a centerpoint of each sensor. Further, electrodermal sensors 424, 426 may bespaced apart from the heat source by distance 446, which equals about 10mm to about 20 mm, about 20 mm to about 30 mm, about 30 mm to about 40mm, about 40 mm to about 50 mm, about 50 mm to about 60 mm, about 60 mmto about 70 mm, about 70 mm to about 80 mm, about 80 mm to about 90 mm,about 90 mm to about 100 mm, measured from a center point of the sensorand a center point of the heat source.

As shown in FIG. 56 as one example, electrodermal activity (EDA) of askin surface of a user may be measured overtime. Left side and rightside electrodermal activity may be measured over time and compared. FIG.56 shows left and right side electrodermal activity including events(shown as triangles) potentially indicative of an anomalous biologicevent. A signal collected by an electrodermal activity sensor may beprocessed to extract one or more features. For example, as shown in FIG.57, one or more features may include a rise time (i.e., start of the SCRto the apex), an amplitude (i.e., EDA at apex minus an EDA at start ofthe SCR), a skin conductance response (SCR) width (i.e., between the 50%of the amplitude on the incline side and 50% of the amplitude on thedecline side), a decay time (i.e., time from apex to 50% of theamplitude), an area under the curve (i.e., SCRwidth multiplied byamplitude), Maximum derivative of SCR, and/or an apex value.

FIG. 63 shows a method 6300 of analyzing EDA data, and FIGS. 64-65 showrepresentative EDA data. A method 6300 for analyzing EDA data includes:receiving signals from one or more EDA sensors (e.g., as shown in FIG.56) S6310; detecting and/or removing one or more artifacts (e.g., asshown in FIG. 56) S6320; calculating or extracting one or more skinconductance response (SCR) features (e.g., as shown in FIG. 57) S6330;calculating a mean or average of one or more features S6340; andcalculating an SCR for a period of time S6350. For example, SCRamplitude is shown graphically in FIG. 65 for one-minute intervals. Asshown, for this individual, SCR amplitude varies over time andasymmetrically (i.e., comparing right vs. left response). Further, ifthe SCRs per minute are compared for left and right responses, as shownin FIG. 64, the SCR per minute varies over time and asymmetrically.

In any of the embodiments described herein, a wearable system or devicefor detecting anomalous biologic events may include one or more motionsensors 436 configured to measure a motion of a body portion to whichthe wearable system is coupled, as shown in FIG. 43. For example, theone or more motion sensors may measure an acceleration in six or ninedegrees of freedom. As described elsewhere herein, a wearable system ordevice for detecting stroke may, in combination with measuring avasodilation response in response to application of heat, may measureasymmetrical movement or tremors of the right and left limbs. One ormore motion sensors may be positioned anywhere on the wearable device.For example, in one embodiment, a motion sensor is positioned in or onthe first surface. In another embodiment, a motion sensor is positionedin or on the second surface. In another embodiment, a motion sensor ispositioned in between the first and second surfaces. In anotherembodiment, a motion sensor is positioned on a sidewall of the body ofthe wearable device. In another embodiment, a motion sensor ispositioned adjacent to a vasodilation sensor or temperature sensor ofthe system, for example concentrically surrounded by the heat source, asshown in FIG. 43.

The heat source of the wearable device or system 400 may be cooled inbetween heating cycles to ensure a return to baseline or substantiallybaseline of the vasodilation response of the skin surface in betweenheating cycles. As such, the heat source may be cooled by an airflowsystem (e.g., fan), a vacuum or vibrating mechanism configured todisplace or pull or move environmental air across the heat source (e.g.,solenoid and diaphragm, oscillating piezo element), etc. In oneembodiment, as shown in FIGS. 40-43, a wearable system or device fordetecting an anomalous biologic event includes first 404 and second 402surfaces that together define a cavity 406 therebetween to provideairflow between the first 404 and second 402 surfaces. The cavity 406defined by the first 404 and second 402 surfaces physically separatesthe heat source 410 from the hardware processor 409 positioned on orwithin the first surface 404. The hardware processor 409 can includemicrocontrollers, digital signal processors, application specificintegrated circuit (ASIC), a field programmable gate array (FPGA) orother programmable logic device, discrete gate or transistor logic,discrete hardware components, or any combination thereof designed toperform the functions described herein. The cavity 406 functions toexpose the heat source 410 to ambient or environmental or surroundingair to cool the heat source 410 to a temperature that approaches,substantially equals, or equals a temperature of the air in theenvironment or an ambient temperature. The cavity 406 may be an emptyspace, an interstitial space, a space that houses one or morecomponents, etc. In some embodiments, cavity 406 formed by the first 404and second 402 surfaces is open to ambient air or environmental air suchthat the sidewalls 405 that couple together the first 404 and the second402 surfaces are opposite one another so that the cavity 406 is open tothe environmental air on opposing sides, as shown in FIGS. 40-41.Alternatively, the sidewalls 405 are connected to one another andadjacent to one another so that the cavity is open to the environmentalair on adjacent or connected sides.

For example, in some embodiments, the cavity 406 defined by the first404 and second 402 surfaces has sufficient volume to facilitate coolingof the heat source 410 in between heating cycles. Alternatively, oradditionally, the cavity 406 may further include an airflow system,vacuum or vibrating mechanism, or other airflow mechanism to promoteairflow through the cavity 406 to reduce a temperature or cool the heatsource 410.

In some embodiments of a wearable system or device, the device includesa port 420 for electrically coupling the device to a power source, forexample to charge a battery 407 in the device. Additionally, oralternatively, port 420 electrically couples the wearable device to anexternal or remote computing device (e.g., laptop, desktop, server,workstation, etc.) to download data from the device or upload systemparameters or install updates to the wearable device. The wearabledevice may further include one or more user input elements 418 to poweron and off the device; to input user specific reactions, features, orcharacteristics, to customize an interface or functionality of the userdevice, etc.

In some embodiments, as shown in FIG. 45, a wearable system fordetecting an anomalous biologic event includes a first system or device400 positioned on a left limb of a user and a second system or device500 positioned on a right limb of the user. The first and second devices400, 500 may measure similar parameters or features so that theparameters or features are comparable over time and/or on anevent-by-event basis to detect asymmetrical biologic responses. Forexample, a hardware processor as part of the system or communicativelycoupled to the devices (e.g., laptop 450 or mobile computing device 46)may be configured to compare right side blood volume signals (e.g., inresponse to an application of heat) to left side blood volume signals(e.g., in response to application of heat) to determine whether theanomalous biologic event has occurred. The right and left side bloodvolume signals may be compared to a baseline right and left side bloodvolume signals, respectively, to account for any asymmetrical baselinedifferences that may exist between the left and right sides. Further, amethod performed by the hardware processor may include synchronizing thesignals received from the left limb and the right limb in time; andcomparing the synchronized signals from the left limb and the right limbto determine whether the anomalous biologic event occurred.

Turning now to FIG. 44, which shows a coupling element 408, configuredto couple a wearable system for detecting an anomalous event to a limbor body portion of a user. For example, the coupling element may be atensionable band for coupling a detection system or device to a limb orbody portion of a user. The tensionable band is formed of or comprises astretchable material (e.g., silicone, rubber, Lycra, Spandex, Elastane,neoprene, leather, fabric, etc.). Alternatively, a portion or section440 of the coupling element may be stretchable, such that thestretchable portion or section 400 can be extended or retracted byapplying varying amounts of tension to the coupling element.Accordingly, the coupling element may be adjustable so that the couplingelement fits a variety of body portion shapes and sizes. For example,the coupling element may have an adjustable circumference. The couplingelement may further include a visual indicator 438 to indicate when oneor more of: the heating element, the skin temperature sensor, the bloodvolume sensor, or a combination thereof is sufficiently coupled to theskin surface to enable accurate sensor readings.

Referring to FIG. 37, a system for detecting stroke may include collectdata from one or more sources, for example a contact-based source, anon-contact-based source, and a source that stimulates a response andthen measures the response output. As shown in FIG. 37, the system mayinclude a main station or docking station and/or measurement station forone or more measurement devices. For example, a heart rate monitor,devices for measuring asymmetrical responses or effects (e.g., watchesworn on each wrist), etc. may be included in the system. The system maybe portable such that is may be positioned in a mobile stroke detectionunit for rapid detection of stroke or positionable in homes of high-riskpatients.

For example, as shown in FIG. 8, a method of detecting tremors (i.e.,asymmetrical wrist movement) includes: measuring an acceleration in x,y, and/or z planes of two limbs (e.g., two arms or two legs) of anindividual; measuring a distance in x, y, and/or z planes of the twolimb of the individual; and calculating a movement of each limit,relative to the other limit, of the individual. In some embodiments,symmetrical movement is indicative of healthy, non-stroke movement, andasymmetrical movement is indicative of a tremor or a stroke event.Exemplary acceleration data (XYZ) is shown in FIG. 9; distance data(XYZ) in FIG. 10; and distance (MM/S; movement) data in FIG. 11. In someembodiments, a specific pattern of time series movements is unique to anindividual and classified as a tremor based on data collected over time.For example, tremor data may be collected for a number of hours,including wake cycles and sleep cycles. The statistical modeling of atremor then becomes a signature for each patient. This signature alsoallows a baseline to be set for each patient. Again, this baselinebehavior may be unique to an individual, and even to the ‘awake’ and‘sleep cycles’ of the individual.

As shown in FIG. 26, an application downloaded and/or stored on ahardware component of a stroke detection system or a computing devicecollates and analyzes acceleration and distance data sensed by a sensor,for example an accelerometer. The comparison of two data sets (i.e.,Test Run 1 and Test Run 2) derived from devices located on the two limbs(e.g., wrists) of the user is shown in FIG. 26. For example, anapplication on a computing device may be configured to compare twoacceleration data sets (FIGS. 27, 32); two distance data sets (FIGS. 28,31); and two movement data sets (FIGS. 29, 30) from devices positionedon two wrists of a user. As shown in FIGS. 29-30, an application on acomputing device may further include a zoom feature, for example, forviewing a subset of the total data collected during a period of time(e.g., overnight, during a tremor instance, etc.).

In some embodiments of a device for detecting tremors or asymmetricalmotion, the device may include a feedback mechanism (e.g., visual,haptic, or audio) when a threshold has been reached or surpassed orvarious comparison criteria have been met, for example when a currentmovement pattern matches a previously identified tremor pattern for theindividual. In some embodiments, a mobile computing devicecommunicatively coupled to a movement sensor or wearable devicegenerates a vibration signal in the wearable device, sensor, and/orcomputing device if the comparison between the two signals exceeds apredefined threshold.

To determine which embodiments would be best for stroke detection,several factors may be considered: alert 911 capability; passivemonitoring; detection when patient is alone; and detection when patientis sleeping. Additional factors may include, but not be limited to:fully mobile; patient specific algorithm; active patient engagementafter a passive alert; detection for the cognitively impaired patient;detection for prior stroke patient; detection of all strokes includingposterior; diagnose type of stroke; passive monitor that wakes thepatient up; and commence stroke treatment. For example, if a possiblestroke event is detected, a wearable system may initiate a tactile,auditory, and/or visual alert to determine whether the user isconscious, unconscious, experiencing other stroke symptoms, etc. If thepatient does not respond in a predetermined time window, a caregiver,emergency services, physician, etc. may be alerted to the stroke event.The wearable system can be linked to a clinician computing system. Thealert can be transmitted directly to the clinician computing system thatmay prompt a telemedicine assessments. The clinician may work up an NIHStroke Score assessment in response to the alert and/or data receivedfrom the wearable system. In some instances, the wearable system can byitself or in conjunction with a personal computing system enableself-assessment by walking the person and/or available witnesses througha FAST (Facial drooping, Arm weakness, Speech difficulties and Time)assessment.

In some instances, the wearable system can transmit a signal to theuser's home automation system or to at least one electronically enableddoor lock to unlock at least one door and/or disable the user's homealarm system in response to an alert for the stroke event. The wearablesystem can also initiate transmission of a floor plan access pathwayleading from an access point of entry to the location of the patient, inthe home or facility where the user has had indicium of a potentialstroke. The location of the patient can be determined based on a localarea network or differential GPS. In some embodiments, a strokedetection device or system may trigger an audible alarm to alert apatient or caretaker, for example while sleeping, that a stroke eventhas occurred. The audible alarm can also enable emergency services tolocate patient when they enter home. All of these measures can help toreduce the time it takes for the emergency services or caregivers toreach the patient.

The home automation system can also include smart displays and smartspeakers. These smart displays and speakers can be used to conveyinformation to emergency medical response personnel, such as theidentification of which medications the patient should be taking and, ifavailable, information about whether they are compliant with prescribedregimens. Information such as the identity of physicians, medicalhistory, allergies, and the existence of medical care power of attorneyor advance directives associated with the patient may also be conveyed.

Furthermore, when alerting emergency services or physicians, dataincluding medical history may be transmitted directly to emergencyservices or physician computing systems, either directly from thewearable system or from a remote memory, initiated by a signal from thewearable system. In addition to alerts, the wearable system can alsoinstruct a user to undertake or automatically activate certain stroketreatments. Stroke treatments can include inducing hypothermia toprovide a neuro-protectant for the patient. The wearable system cantrigger inhalation of cooling gases, activation of a cooling helmet,activation of an ultrasonic helmet to break up cloths, or ingestion ortriggering administration of a drug patch or pill. The trigger can beinstructions to the patient or medical responder, or automaticactivation. In some instances, for Ischemic strokes, the wearable systemcan trigger mechanisms to increasing blood pressure and vasodilate bloodvessels (through some of the mechanisms discussed above).

Treatments responsive to the detection of a potential stroke can beinitiated by the patient if they are conscious and able, or by themedical response personnel via the home automation system. Patients in aparticular high risk category may have previously been fitted with awearable treatment device which can be activated automatically inresponse to a signal indicating the detection of a potential stroke, oractivated by medical personnel following clinical examination which wasinitiated by an alert from the wearable system.

In some embodiments, a stroke detection device or system may trigger anaudible alarm to alert a patient or caretaker, for example whilesleeping, that a stroke event has occurred. The audible alarm can alsoenable emergency services to locate patient when they enter home.

In any of the embodiments described herein, a stroke detection device orsystem may record an onset of a stroke event and/or provide a “lastknown well” indicator to help inform treatment decisions.

In some embodiments, a system for detecting stroke includes a dataprocessing module. The data processing module may be configured toextract a pattern. The pattern may suggest any ischemic or hemorrhagicepisode very early, possibly imminently prior to an actual stroke event.In some embodiments, the pattern may be empirically determined, forexample based on a population wide analysis, cohort analysis, and/orindividual analysis of signals, which are analyzed for parameters and/orpatterns indicative of stroke onset. In some embodiments, signalprocessing may employ signal processing tools, for example filtering,extracting, digitizing, data de-convolution, machine learning, and/orother methods known in the art. Specifically, the signal processing mayuse higher order statistics to ascertain hidden patterns in data. Use ofhigher order statistics, known as cumulants, and their Fourier spectra,often termed poly spectra, not only reveal the amplitude information inthe higher order (such as those carried by power spectra or autocorrelation) but may also include phase information. Phase informationcan reveal salient features of the data, otherwise unattainable fromsimple harmonic analysis. Another important feature of the polyspectrais the fact that they are blind to Gaussian processes. As a result, theycan automatically handle Gaussians processes and thus improve signal tonoise ratio, allowing novel detection. In some embodiments, a number ofspectrums and their manipulations may be selected in order to identifyhidden patterns in the sensed signals, for example BP(t), ECG(t) etc.

For example, as shown in FIGS. 53-55, a wearable system may collectelectrocardiogram (ECG) data, pre-process the data, identify peaks inthe data, and apply a decision logic to the data. FIG. 54 showselectrocardiogram data collected over time. FIG. 55 shows extracted R-Rintervals from the electrocardiogram data (i.e., time between beatsshown in milliseconds). The method 5300 shown in FIG. 53 may be used tocalculate a heartbeat and/or a heart rate variability (i.e., specificchanges in time between successive heart beats) of an individual. Asshown in FIG. 53, ECG data is input into the method 5300, which detectsQRS complexes (i.e., ventricular depolarization and the main spike in anECG signal) in electrocardiographic signals. Preprocessing at blockS5310 includes apply signal processing techniques for QRS featureextraction. For example, preprocessing may be applied to reduce theinfluence of muscle noise, powerline interference, baseline wander,and/or T-wave interference. Peak Detection at block S5320 includes QRSpeak detection with adaptive threshold, for example. Each potential peakis compared to a baseline value. A baseline skin temperature isestablished by measuring unstimulated skin for a period of time. Oncethe baseline is determined, the stimulus (e.g., application of heat) caneither reach a time limit or a temperature limit. The temperature limitcan be absolute or relative to the baseline skin temperature. Thebaseline value is updated according to the amplitude of the detectedpeak. Decision Logic at block S5330 classifies the current peak as QRS,T-wave, or error beat, using the peak slope and/or peak-to-peakinterval.

As shown in FIGS. 58-62, electrocardiogram data may be processed viaseveral methods to extract various features, calculate one or morefeatures (e.g., heart rate variability, heart rate, total power, etc.),etc. For example, a time domain analysis (FIG. 58), a geometricalanalysis (FIG. 59), a frequency domain analysis (FIG. 60), and/or anonlinear analysis (FIG. 61) analysis may be used.

As shown in FIG. 58, ECG data (e.g., FIG. 54) is fed into method 5800.The method includes: receiving ECG data of a user using an ECG;detecting beats in the ECG data (e.g., detect R-peaks in the ECG data)S5810; identifying and correcting irregular beats (e.g., missed, extra,and ectopic beats; uses neighboring beats to correct each beat) S5820;identifying intervals between normal R-peaks (i.e., NN Interval TimeSeries (NNIs) S5830; preprocessing the data (e.g., corrects outliers ofNNIs) S5840; and performing one or more analyses S5850. For example, atime domain analysis, as shown in FIG. 59 may be used to calculate heartrate (e.g., 60 divided by the mean of NNIs); the standard deviation ofNNIs (SDNN); the root mean square of successive differences (RMSSD); andthe percentage of adjacent NNIs that differ from each other by more than50 ms (pNN50). Further, for example, a frequency domain analysis, asshown in FIG. 61, may be used to calculate a relative power (e.g.,relative power of each frequency band (VLF/Total, LF/Total, HF/Total));a normalized power (e.g., normalized powers of the LF and HF frequencybands (LF/(LF+HF), HF/(LF+HF)); an LF/HF Ratio (e.g., LF power/HFpower); and/or a total power (e.g., total power over all frequencybands). Further, for example, a geometrical analysis, as shown in FIG.60, may be used to calculate a baseline width of the interpolatedtriangle (TINN); and/or the ratio between the total number of NNI andthe maximum of the NNI histogram distribution (i.e., triangular index).Further, for example, as shown in FIG. 62, a nonlinear analysis may beused to perform a Poincare Analysis (i.e., analyze Poincare plot ofNNIs-SD1, SD2, SD Ratio, Ellipse Area); a DFA (Detrended FluctuationAnalysis (i.e., short and long-term fluctuations of NNIs); and/or anEntropy Analysis (i.e., computes approximate entropy, sample entropy,and fuzzy entropy of NNIs).

In some embodiments, the data processing module may use the continuouslymonitored or intermittently monitored physiological signals todifferentiate changes from healthy “learned” or individualized baselinedata. For example, the module may continuously learn the signals comingfrom an individual patient rather than using a statistical average takenfrom many patients. A custom reference signal may significantly improveminute changes in the physiological signals for an individual patient.In some embodiments, the physiological parameters may be processed as afunction of time that includes the shape of the curve changes, includinghidden harmonics, changes in higher order derivatives, etc.

FIG. 33 shows one embodiment of various components of a data processingmodule. The core engine for one embodiment of the data processing modulemay include one or more of the following parameters: fast processing,support for sophisticated analytics, real time stream processing,integration with both NoSQL and RDBMS, and integration with Hadoop.

The data processing module may employ various machine learning methodsto identify patterns, extract patterns, identify parameters indicativeof stroke onset, etc. Machine learning can be broadly defined as theapplication of any computer-enabled algorithm that can be appliedagainst a data set to find a pattern in the data. A machine-learningalgorithm is used to determine the relationship between a system'sinputs and outputs using a learning data set that is representative ofall the behavior found in the system. This learning can be supervised orunsupervised. For example, a simple neural network called a MultilayerPerceptron (MLP), as shown in FIG. 34, may be used to model variousparameters or patterns of an individual, for example while sleeping.Each node is a neuron that uses a nonlinear activation function. Such asimple neural network may be used to distinguish data that are notlinearly separable. In some embodiments, as shown in FIG. 35, a deeplearning network may be used. A deep learning network may comprise aLeverage Recurrent Neural Networks (RNN) implementation, as shown inFIG. 36. The system creates layers of interconnected networks, whereeach layer corresponds to a time slice. RNN are proven highly effectivein handling time series data, assumes training inputs are timedependent, capable of accurately modeling/predicting changes throughtime, capable of generating an actual output value for a data pointversus giving just a range, and each time slice is its own feed forwardnetwork—specified by a user.

In some embodiments, a system for providing comprehensive stroke carecomprises one or more of: educational resources tailored to the patientbased on demographics, type of stroke, co-morbidities, medications, etc;management tools to assist with the dramatic changes in lifestyle, suchas reminders (e.g., medications, rehabilitation appointments, etc.),collaborative care resources (e.g., for spouse, doctor, physicaltherapist, caretaker, etc.), activity tracking with continuous datacollection via a wearable, fitness tracking and guided meditation,stroke risk level assessment, etc.; community with others as part of thefirst national stroke survivor network where stroke survivors can giveand receive support and encouragement connecting both patients andcaregivers, “check in” with others in your group to make sure they aremaking progress towards their goals and are doing well mentally, sharestories and relate to others, receive telemedicine/rehab resources witha speech therapist or mental health counselor; patient rehab andmonitoring, or other enabling technologies; set recovery goals and trackprogress, cognitive evaluation tools, etc.; stroke Detection to alertcaretakers via call/message, communication tools for patients withaphasia, etc.

EXAMPLE 1

Various functional symptoms, quantitative markers, and blood/fluidproducts were scored for their ability to detect stroke. The scoringcriteria were the following: should be grounded in scientific rationale,should be highly sensitive (>90%), should only have very few falsepositives (<10%), and stroke detection should be passive (automatic).Each of these parameters were scored from 0 to 5, except for passivedetection which was scored on a scale of 0 (active detection) to 1(passive detection). The score was then multiplied by a weight factor,shown in Table 1 below, and all the weighted factors summed to yield atotal score.

As shown below in Tables 2 and 5, the functional symptoms with thehighest total score were facial muscle weakness, unilateral weakness,limited visual field, gaze altered, and speech change. Of thesefunctional symptoms, only facial muscle weakness, unilateral weakness,and speech change can be detected passively.

TABLE 1 Analyzed Factors and Associated Weights Factor (score each on(0-5)) Weighting Factor Should be grounded in scientific rationale 5Should be highly sensitive (>90%) 5 Should only have very few FPs (<10%)2 Stroke detection should be passive (automatic) 4

TABLE 2 Analysis of Functional Symptoms of Stroke Detection passive?Functional Time Sample Scientific (passive = 1, Total Symptom PeriodEmbodiment rationale active = 0) Sensitivity Specificity Score SpeechChange During, Amazon Alexa devices, 5 1 4 3 55 after Smart speakers,Smartwatch, external microphone coupled to 3^(rd) party device SpeechDuring, Amazon Alexa 5 0 4 2 49 Comprehension after devices, Smartspeakers, Smartwatch Text During, Phone App, 3 0 4 2 39 Comprehensionafter Tablet App Consciousness During Camera, Wearable, 4 1 3 2 43Smartwatch Coordination/ During Camera, Wearable, 3 0 3 2 34 DirectionsSmartwatch Facial Muscle During, Camera, Wearable 5 1 5 4 62 Weaknessafter Arm Weakness During Camera, Wearable 5 1 4 3 55 Body Weakness -During Camera, Wearable 3 0 3 3 36 Grip Leg weakness During Camera,Wearable 4 1 3 2 43 Foot weakness During Camera, Wearable 4 1 3 2 43Unilateral During Camera, Wearable 5 1 5 4 62 weakness DifficultyDuring, Camera, Wearable 4 1 2 2 38 Walking after Vertigo During Camera,Wearable 4 0 4 2 44 Sudden Vision During Amazon Alexa 5 0 4 4 53Problems devices, Phone app Limited Visual During Amazon Alexa 5 0 5 356 Field devices, Phone app Gaze Altered During Camera, Phone app 5 0 53 56 Thunderclap Before, Amazon Alexa 5 0 4 3 51 Headache during,devices, Phone app after Nuchal rigidity Amazon Alexa 5 0 3 3 46 (napeof neck) devices, Phone app Respiration Before, Wearable device, 3 1 2 233 during non-contact Doppler radar, Eulerian video processingtechniques Blood Pressure Before, Wearable device 3 1 4 2 43 during(continuous use; periodic use)

As shown in Tables 3 and 5, the quantitative markers with the highesttotal score were cerebral blood flow, EEG asymmetry, carotid arterystenosis, volumetric impedance spectroscopy, and limb asymmetry. Ofthese quantitative markers, all were considered to be detectablepassively.

TABLE 3 Analysis of Quantitative Symptoms of Stroke Detection passive?Time Sample Scientific (passive = 1, Total Marker Period Embodimentrationale active = 0) Sensitivity Specificity Score Volumetric During,after Wearable, implant 5 1 3 4 52 impedance spectroscopy EEG asymmetryDuring, after Wearable, implant 5 1 4 4 57 Brain perfusion During, afterWearable 4 1 3 4 47 Skin temperature After Wearable, IR 4 1 3 2 43imaging Hyperhidrosis After Wearable 3 1 4 2 43 Limb asymmetry During,after Wearable, camera 4 1 4 4 52 Drift and During, after Camera 4 0 4 448 pronation test Cutaneous blood After Wearable, camera 3 1 3 3 40 flowMuscle tone During, after Wearable, camera 3 1 4 3 45 Heartrate AfterWearable, implant, 3 1 3 3 40 variability non-contact, Doppler radarFacial surface During, after Wearable, implant 4 1 4 4 52 EMG Cerebralblood During, after Wearable, implant 5 1 5 5 64 flow (CBF) Carotidartery During, after Implant 5 1 4 3 55 stenosis Salivary cortisolDuring, after Wearable, implant 3 1 2 2 33 Neuron specific During, afterWearable, implant 4 1 4 4 52 enolase (NSE) Salivary NSE During, afterWearable, implant 4 1 4 4 52

As shown in Tables 4 and 5, the products with the highest total scorewere Cornell University's products, SMARTChip, and ReST. Of these, nonewere considered to be passive detection.

TABLE 4 Analysis of Products for Stroke Rapid Diagnosis Diagnosispassive? Time to Scientific (passive = 1, Total Product Detect Notesrationale active = 0) Sensitivity Specificity Score CoaguCheck <1 min Toshorten 2 0 2 2 24 (Roche) door-needle time; determine to start TPAfaster HemoChron ~few mins To shorten 2 0 2 2 24 (ITC) door-needle time;determine to start TPA faster iSTAT <2 mins To shorten 2 0 2 2 24(Abbott) door-needle time; determine to start TPA faster CornellUniversity not known Distinguish stroke 4 0 3 5 45 from stroke mimicsReST <10 mins Initial stroke vs 3 0 3 3 36 (Valtari Bio Inc) no strokediagnosis SMARTChip ~few mins Stroke vs no stroke 3 0 4 2 39 (SarissaBiomedical) using one drop of blood

TABLE 5 Results Total Functional Score Symptom #1 62 Facial MuscleWeakness #2 62 Unilateral weakness #3 56 Limited Visual Field #4 56 GazeAltered #5 55 Speech Change Total Quantitative Score Symptom #1 64Cerebral blood flow (CBF) #2 57 EEG asymmetry #3 55 Carotid arterystenosis #4 52 Volumetric impedance spectroscopy #5 52 Limb asymmetryTotal Blood Score Organization #1 45 Cornell University #2 39 SMARTChip(Sarissa Biomedical) #3 36 ReST (Valtari Bio Inc)

Taken together, a multivariate system for stroke detection may includedetecting one or more of: cerebral blood flow, EEG asymmetry, carotidartery stenosis, volumetric impedance spectroscopy, limb asymmetry,facial muscle weakness, unilateral weakness, and speech change. In someembodiments, these various parameters may be measured at a variety oflocations and/or times to determine stroke onset, occurrence, or afteraffects.

EXAMPLE 2

Symmetrical and asymmetrical acceleration and distance were measuredusing an Apple® Watch and displayed in a graphic representation (FIGS.9-11, 27-32) in an application on a computing device. For this example,the implementation also measures the resolution of the Apple® Watchaccelerometer sensor and existing API capabilities.

For this example, the device was worn on a user's wrist. Anyacceleration of the wrist was recoded and saved in the onboard database,including acceleration in x-, y- and z-axes. The computing device has a“sync” function that allows the data to be transferred to a computingdevice for analysis. Tables 6-8 show acceleration data, distance data,and calculated movement data (i.e., distance traveled), respectively,acquired using an Apple® Watch worn on each wrist of a user. Data valueswere recorded at various time points, as shown in FIGS. 9-11, 27-32.

TABLE 6 Acceleration (XYZ) of a Wrist 30 60 90 120 150 Acceleration Xaxis ~10 ~0 ~0 ~15 ~0 Acceleration Y axis ~10 ~0 ~0 ~15 ~0 AccelerationZ axis ~10 ~0 ~0 ~15 ~0

TABLE 7 Distance Measurement of a Wrist 30 60 90 120 150 Acceleration Xaxis ~10 ~0 ~0 ~15 ~0 Acceleration Y axis ~10 ~0 ~0 ~15 ~0 AccelerationZ axis ~10 ~0 ~0 ~15 ~0

TABLE 8 Movement Calculation of a Wrist 10 20 30 40 Description Label143 51 247 207

Taken together, a system for stroke detection may include detecting oneor more of: acceleration in x-, y- and/or z-axes; and/or distance in x-,y- and/or z-axes; and, in some embodiments, calculating a distancetraveled (i.e., movement) to determine asymmetrical limb movement, gait,etc. possibly indicative of a stroke event.

The systems and methods of the preferred embodiment and variationsthereof can be embodied and/or implemented at least in part as a machineconfigured to receive a computer-readable medium storingcomputer-readable instruction. The instructions are preferably executedby computer-executable components preferably integrated with the systemand one or more portions of the hardware processor on the device fordetecting stroke and/or computing device. The computer-readable mediumcan be stored on any suitable computer-readable media such as RAMs,ROMs, flash memory, EEPROMs, optical devices (e.g., CD or DVD), harddrives, floppy drives, or any suitable device. The computer-executablecomponent is preferably a general or application-specific hardwareprocessor, but any suitable dedicated hardware or hardware/firmwarecombination can alternatively or additionally execute the instructions.

As used in the description and claims, the singular form “a”, “an” and“the” include both singular and plural references unless the contextclearly dictates otherwise. For example, the term “signal” may include,and is contemplated to include, a plurality of signals. At times, theclaims and disclosure may include terms such as “a plurality,” “one ormore,” or “at least one;” however, the absence of such terms is notintended to mean, and should not be interpreted to mean, that aplurality is not conceived.

The term “about” or “approximately,” when used before a numericaldesignation or range (e.g., to define a length or pressure), indicatesapproximations which may vary by (+) or (−) 5%, 1% or 0.1%. Allnumerical ranges provided herein are inclusive of the stated start andend numbers. The term “substantially” indicates mostly (i.e., greaterthan 50%) or essentially all of a device, substance, or composition.

As used herein, the term “comprising” or “comprises” is intended to meanthat the devices, systems, and methods include the recited elements, andmay additionally include any other elements. “Consisting essentially of”shall mean that the devices, systems, and methods include the recitedelements and exclude other elements of essential significance to thecombination for the stated purpose. Thus, a system or method consistingessentially of the elements as defined herein would not exclude othermaterials, features, or steps that do not materially affect the basicand novel characteristic(s) of the claimed disclosure. “Consisting of”shall mean that the devices, systems, and methods include the recitedelements and exclude anything more than a trivial or inconsequentialelement or step. Embodiments defined by each of these transitional termsare within the scope of this disclosure.

The examples and illustrations included herein show, by way ofillustration and not of limitation, specific embodiments in which thesubject matter may be practiced. Other embodiments may be utilized andderived therefrom, such that structural and logical substitutions andchanges may be made without departing from the scope of this disclosure.Such embodiments of the inventive subject matter may be referred toherein individually or collectively by the term “invention” merely forconvenience and without intending to voluntarily limit the scope of thisapplication to any single invention or inventive concept, if more thanone is in fact disclosed. Thus, although specific embodiments have beenillustrated and described herein, any arrangement calculated to achievethe same purpose may be substituted for the specific embodiments shown.This disclosure is intended to cover any and all adaptations orvariations of various embodiments. Combinations of the aboveembodiments, and other embodiments not specifically described herein,will be apparent to those of skill in the art upon reviewing the abovedescription.

EXAMPLE EMBODIMENTS

A wearable system for detecting an anomalous biologic event in a person,comprising one or more of the following:

-   -   a body having a first surface opposite a second surface in        contact with a skin surface of a person;    -   a heat source in communication with the skin surface, wherein        the heat source is configured to heat the skin surface to a        target temperature;    -   a skin temperature sensor positioned on the second surface and        configured to measure a temperature of the skin surface in        contact with the heat source;    -   a blood volume sensor positioned on the second surface and        configured to measure a blood volume of the skin surface; and    -   a hardware processor communicatively coupled to the heat source,        the blood volume sensor, the skin temperature sensor, and an        environmental temperature sensor configured to measure a        temperature of the environment around the wearable system,        wherein the hardware processor is configured to:    -   receive a baseline blood volume signal from the blood volume        sensor,    -   output a heating signal to the heat source to initiate a heating        cycle, wherein the heating cycle comprises heating the skin        surface to the target temperature,    -   receive a second blood volume signal from the blood volume        sensor in response to the skin surface reaching the target        temperature,    -   compare the second blood volume signal to the baseline blood        volume signal, and    -   determine whether an anomalous biologic event has occurred based        on the comparison.

The wearable system of any embodiment disclosed herein, wherein thesecond blood volume signal comprises a set of blood volume signals, suchthat the blood volume of the skin surface is measured repeatedly before,during, and after a heating cycle of the heat source.

The wearable system of any embodiment disclosed herein, wherein thesecond blood volume signal comprises a plurality of blood volumesignals, such that the blood volume of the skin surface is measuredcontinuously before, during, and after a heating cycle of the heatsource.

The wearable system of any embodiment disclosed herein, wherein hardwareprocessor is further configured to receive the second blood volumesignal after the target temperature is reached, after a predeterminedlength of time has expired, or after one or more heating cycles haveconcluded.

The wearable system of any embodiment disclosed herein, whereincomparing comprises calculating a baseline ratio of alternating current(AC) to direct current (DC) for the baseline blood volume signal and asecond ratio of AC to DC for the second blood volume signal andcomparing the baseline ratio to the second ratio.

The wearable system of any embodiment disclosed herein, wherein theenvironmental temperature sensor is positioned on the first side of thebody of the wearable system.

The wearable system of any embodiment disclosed herein, furthercomprising a remote computing device communicative coupled to thewearable system and comprising the environmental temperature sensor.

The wearable system of any embodiment disclosed herein, wherein theremote computing device comprises one of: a laptop, cellular device, aworkstation, a server, a desktop computer, a personal digital assistant,a second wearable system or device, or a netbook.

The wearable system of any embodiment disclosed herein, wherein the heatsource is positioned on the second surface of the body.

The wearable system of any embodiment disclosed herein, wherein thehardware processor is further configured to:

-   -   receive baseline temperature signals from the skin temperature        sensor and the environmental temperature sensor,    -   determine the target temperature based on the baseline        temperature signals, and    -   determine whether the target temperature is below a maximum        temperature value.

The wearable system of any embodiment disclosed herein, wherein thehardware processor is further configured to cycle the heat source tomaintain the target temperature.

The wearable system of any embodiment disclosed herein, furthercomprising one or more electrodermal activity sensors positioned on thesecond surface.

The wearable system of any embodiment disclosed herein, wherein the oneor more electrodermal activity sensors are spaced apart from the heatingelement by about 0.25 inches to about 4 inches.

The wearable system of any embodiment disclosed herein, furthercomprising one or more motion sensors configured to measure a motion ofa body portion to which the wearable system is coupled.

The wearable system of any embodiment disclosed herein, wherein thefirst and second surfaces define a cavity therebetween to provideairflow between the first and second surfaces.

The wearable system of any embodiment disclosed herein, wherein thehardware processor resides on or within the first surface.

The wearable system of any embodiment disclosed herein, wherein thecavity defined by the first and second surfaces physically separates theheat source from the hardware processor on or within the first surface.

The wearable system of any embodiment disclosed herein, wherein thecavity defined by the first and second surfaces has sufficient volume tofacilitate cooling of the heat source in between heating cycles.

The wearable system of any embodiment disclosed herein, wherein theanomalous biologic event comprises a stroke event.

The wearable system of any embodiment disclosed herein, wherein thewearable system is positioned on a left limb of a user and a secondwearable system is positioned on a right limb of the user, wherein thesecond wearable system comprises a second heating element, a second skintemperature sensor, and a second blood volume sensor, wherein thehardware processor is further configured to compare right side bloodvolume signals to left side blood volume signals to determine whetherthe anomalous biologic event has occurred.

The wearable system of any embodiment disclosed herein, wherein thehardware processor is further configured to:

-   -   synchronize the signals received from the left limb and the        right limb in time; and    -   compare the synchronized signals from the left limb and the        right limb to determine whether the anomalous biologic event        occurred.

The wearable system of any embodiment disclosed herein, wherein thecomparison takes into account a baseline difference between the leftlimb and the right limb.

The wearable system of any embodiment disclosed herein, furthercomprising a tensionable band coupled to the body.

The wearable system of any embodiment disclosed herein, wherein thetensionable band further comprises a visual indicator to indicate whenone or more of: the heating element, the skin temperature sensor, theblood volume sensor, or a combination thereof is sufficiently coupled tothe skin surface to enable accurate sensor readings.

The wearable system of any embodiment disclosed herein, wherein one ormore ends of the tensionable band are coupled to the body at a positionthat is centered with respect to one or more sensors positioned on thesecond surface.

The wearable system of any embodiment disclosed herein, wherein the heatsource is positioned concentrically about one or both of the bloodvolume sensor and the skin temperature sensor.

The wearable system of any embodiment disclosed herein, wherein theblood volume sensor comprises a photoplethysmography sensor or animpedance plethysmographic sensor.

The wearable system of any embodiment disclosed herein, wherein the skintemperature sensor comprises a thermocouple, a resistance temperaturedetector, a thermistor, or an infrared temperature sensor.

The wearable system of any embodiment disclosed herein, furthercomprising a support structure coupled to the heat source and configuredto couple the heat source to the second surface and at least partiallyexpose the heat source to the cavity.

The wearable system of any embodiment disclosed herein, wherein theblood volume sensor is further configured to measure one or more of:heart rate, heart rate variability, or oxygen saturation.

The wearable system of any embodiment disclosed herein, wherein thetarget temperature is individualized to the user.

The wearable system of any embodiment disclosed herein, whereinindividualization of the target temperature comprises receiving a userinput related to perceived temperature of the skin surface.

The wearable system of any embodiment disclosed herein, whereinindividualization of the target temperature is based on signals receivedfrom the blood volume sensor.

The wearable system of any embodiment disclosed herein, wherein the heatsource comprises one of: a heating element or an environmentaltemperature.

The wearable system of any embodiment disclosed herein, wherein thehardware processor is configured to transmit an electronic message to afirst electronic system responsive to the determination of the anomalousbiologic event, said first electronic system configured toelectronically manage a home automation system.

The wearable system of any embodiment disclosed herein, wherein the homeautomation system comprises a door lock and wherein said electronicmessage is configured to instruct the first electronic system to unlockthe door lock.

The wearable system of any embodiment disclosed herein, wherein the homeautomation system comprises a home alarm system and wherein saidelectronic message is configured to instruct the first electronic systemto disable the home alarm system.

The wearable system of any embodiment disclosed herein, wherein the homeautomation system comprises a display and wherein said electronicmessage is configured to instruct the first electronic system to displayuser's medical information.

The wearable system of any embodiment disclosed herein, wherein themedical information comprises medication information and/or medicationregimen compliance.

The wearable system of any embodiment disclosed herein, wherein the homeautomation system comprises a display and wherein said electronicmessage is configured to instruct the first electronic system to displaystroke treatment user interface.

The wearable system of any embodiment disclosed herein, wherein the homeautomation system comprises a speaker system and wherein said electronicmessage is configured to instruct the first electronic system to triggeran audible alarm with the speaker system.

The wearable system of any embodiment disclosed herein, wherein thehardware processor is further configured to alert a third partycomputing system responsive to the determination of the anomalousbiologic event.

The wearable system of any embodiment disclosed herein, wherein thethird party computing system comprises an emergency service system.

The wearable system of any embodiment disclosed herein, wherein thethird party computing system comprises a clinician computing system.

The wearable system of any embodiment disclosed herein, wherein thehardware processor is further configured to initiate treatment protocolresponsive to the detection of anomalous biologic event.

The wearable system of any embodiment disclosed herein, furthercomprising a wearable treatment system and said treatment protocol isconfigured to activate the wearable treatment system.

The wearable system of any embodiment disclosed herein, wherein thewearable treatment system comprises an ultrasonic helmet.

The wearable system of claim 46, wherein the wearable treatment systemcomprises a cooling gas delivery system.

The wearable system of any embodiment disclosed herein, wherein thewearable treatment system comprises a cooling helmet.

A wearable system for detecting an anomalous biologic event in a person,comprising one or more of the following:

-   -   a body having a first surface opposite a second surface in        contact with a skin surface of a person, the first and second        surfaces defining a cavity therebetween to provide airflow        between the first and second surfaces;    -   a heating element positioned on the second surface and        configured to heat the skin surface for a predetermined length        of time;    -   a skin temperature sensor positioned on the second surface and        configured to measure a temperature of the skin surface in        contact with the heating element;    -   a blood volume sensor positioned on the second surface and        configured to measure a blood volume of the skin surface;    -   a hardware processor communicatively coupled to the heating        element, the blood volume sensor, the skin temperature sensor,        and an environmental temperature sensor configured to measure a        temperature of the environment around the wearable system,        wherein the hardware processor is configured to:    -   receive a baseline blood volume signal from the blood volume        sensor,    -   output a heating signal to the heating element to initiate a        heating cycle, wherein the heating cycle comprises heating the        skin surface to a target temperature,    -   receive a second blood volume signal from the blood volume        sensor in response to the skin surface reaching the target        temperature,    -   compare the second blood volume signal to the baseline blood        volume signal, and    -   determine whether an anomalous biologic event has occurred based        on the comparison.

A wearable system for detecting an anomalous biologic event in a person,comprising one or more of the following:

-   -   a body having a first surface opposite a second surface in        contact with a skin surface of a person;    -   a heat source in communication with the skin surface, wherein        the heat source is configured to heat the skin surface to a        target temperature;    -   a skin temperature sensor positioned on the second surface and        configured to measure a temperature of the skin surface in        contact with the heat source;    -   a sensor positioned on the second surface and configured to        measure a parameter of interest of the person; and    -   a hardware processor communicatively coupled to the heat source,        the sensor, the skin temperature sensor, and an environmental        temperature sensor configured to measure a temperature of the        environment around the wearable system, wherein the hardware        processor is configured to:    -   receive a baseline sensor signal from the sensor,    -   output a heating signal to the heat source to initiate a heating        cycle, wherein the heating cycle comprises heating the skin        surface to the target temperature,    -   receive a second sensor signal from the sensor in response to        the skin surface reaching the target temperature,    -   compare the second sensor signal to the baseline sensor signal,        and    -   determine whether an anomalous biologic event has occurred based        on the comparison.

The wearable system of any embodiment disclosed herein, wherein thesensor is selected from the group consisting of: a stretch sensor, anelectrodermal activity sensor, an electrocardiogram sensor, a camera, ora blood volume sensor.

The wearable system of any embodiment disclosed herein, wherein theparameter of interest includes one or more of: a blood pressure, a heartrate, a heart rate variability, a gaze, a facial expression, a skinconductance response, a vasodilation response, or a dilation response.

A wearable system for detecting an anomalous biologic event in a person,comprising one or more of the following:

-   -   a body having a first surface opposite a second surface in        contact with a skin surface of a person;    -   a stimulus source in communication with the skin surface,        wherein the stimulus source is configured to apply a stimulus to        the skin surface;    -   a blood volume sensor positioned on the second surface and        configured to measure a blood volume of the skin surface; and    -   a hardware processor communicatively coupled to the stimulus        source and the blood volume sensor, wherein the hardware        processor is configured to:    -   receive a baseline blood volume signal from the blood volume        sensor,    -   output a stimulus signal to the stimulus source to initiate a        stimulus cycle,    -   receive a second blood volume signal from the blood volume        sensor in response to the initiation of the stimulus cycle,    -   compare the second blood volume signal to the baseline blood        volume signal, and    -   determine whether an anomalous biologic event has occurred based        on the comparison.

The wearable system of any embodiment disclosed herein, wherein thestimulus source comprises a heat source.

The wearable system of any embodiment disclosed herein, wherein thestimulus source comprises an electrical source.

The wearable system of any embodiment disclosed herein, wherein thecomparison comprises determining a change in vasodilation response.

The wearable system of any embodiment disclosed herein, wherein thestimulus source comprises a Peltier cooler.

The wearable system of any embodiment disclosed herein, wherein thesecond blood volume signal comprises a set of blood volume signals, suchthat the blood volume of the skin surface is measured repeatedly before,during, and after the stimulus cycle.

The wearable system of any embodiment disclosed herein, wherein thesecond blood volume signal comprises a plurality of blood volumesignals, such that the blood volume of the skin surface is measuredcontinuously before, during, and after the stimulus cylce.

The wearable system of any embodiment disclosed herein, wherein hardwareprocessor is further configured to receive the second blood volumesignal after a target stimulus is reached, after a predetermined lengthof time has expired, or after one or more stimulus cycles haveconcluded.

The wearable system of any embodiment disclosed herein, whereincomparing comprises calculating a baseline ratio of alternating current(AC) to direct current (DC) for the baseline blood volume signal and asecond ratio of AC to DC for the second blood volume signal andcomparing the baseline ratio to the second ratio.

The wearable system of any embodiment disclosed herein, wherein theblood volume sensor is positioned on the first side of the body of thewearable system.

The wearable system of any embodiment disclosed herein, furthercomprising a remote computing device communicative coupled to thewearable system and comprising the blood volume sensor.

The wearable system of any embodiment disclosed herein, wherein theremote computing device comprises one of: a laptop, cellular device, aworkstation, a server, a desktop computer, a personal digital assistant,a second wearable system or device, or a netbook.

The wearable system of any embodiment disclosed herein, wherein thestimulus source is positioned on the second surface of the body.

The wearable system of any embodiment disclosed herein, wherein thehardware processor is further configured to:

-   -   receive baseline blood volume signals from the blood volume        sensor,    -   determine the target blood volume based on the baseline blood        volume signals, and    -   determine whether the target blood volume is below a maximum        blood volume value.

The wearable system of any embodiment disclosed herein, wherein thehardware processor is further configured to cycle the stimulus source tomaintain the target blood volume.

The wearable system of any embodiment disclosed herein, furthercomprising one or more electrodermal activity sensors positioned on thesecond surface.

The wearable system of any embodiment disclosed herein, wherein the oneor more electrodermal activity sensors are spaced apart from thestimulus source by about 0.25 inches to about 4 inches.

The wearable system of any embodiment disclosed herein, furthercomprising one or more motion sensors configured to measure a motion ofa body portion to which the wearable system is coupled.

The wearable system of any embodiment disclosed herein, wherein thefirst and second surfaces define a cavity therebetween to provideairflow between the first and second surfaces.

The wearable system of any embodiment disclosed herein, wherein thehardware processor resides on or within the first surface.

The wearable system of any embodiment disclosed herein, wherein thecavity defined by the first and second surfaces physically separates thestimulus source from the hardware processor on or within the firstsurface.

The wearable system of any embodiment disclosed herein, wherein thecavity defined by the first and second surfaces has sufficient volume tofacilitate cooling of the stimulus source in between stimulus cycles.

The wearable system of any embodiment disclosed herein, wherein theanomalous biologic event comprises a stroke event.

The wearable system of any embodiment disclosed herein, wherein thewearable system is positioned on a left limb of a user and a secondwearable system is positioned on a right limb of the user, wherein thesecond wearable system comprises a second stimulus source and a secondblood volume sensor, wherein the hardware processor is furtherconfigured to compare right side blood volume signals to left side bloodvolume signals to determine whether the anomalous biologic event hasoccurred.

The wearable system of any embodiment disclosed herein, wherein thehardware processor is further configured to:

-   -   synchronize the signals received from the left limb and the        right limb in time; and    -   compare the synchronized signals from the left limb and the        right limb to determine whether the anomalous biologic event        occurred.

The wearable system of any embodiment disclosed herein, wherein thecomparison takes into account a baseline difference between the leftlimb and the right limb.

The wearable system of any embodiment disclosed herein, furthercomprising a tensionable band coupled to the body.

The wearable system of any embodiment disclosed herein, wherein thetensionable band further comprises a visual indicator to indicate whenone or more of: the stimulus source, the blood volume sensor, or acombination thereof is sufficiently coupled to the skin surface toenable accurate sensor readings.

The wearable system of any embodiment disclosed herein, wherein one ormore ends of the tensionable band are coupled to the body at a positionthat is centered with respect to one or more sensors positioned on thesecond surface.

The wearable system of any embodiment disclosed herein, wherein thestimulus source is positioned concentrically about the blood volumesensor.

The wearable system of any embodiment disclosed herein, wherein theblood volume sensor comprises a photoplethysmography sensor or animpedance plethysmographic sensor.

The wearable system of any embodiment disclosed herein, furthercomprising a support structure coupled to the stimulus source andconfigured to couple the stimulus source to the second surface and atleast partially expose the stimulus source to the cavity.

The wearable system of any embodiment disclosed herein, wherein theblood volume sensor is further configured to measure one or more of:heart rate, heart rate variability, or oxygen saturation.

The wearable system of any embodiment disclosed herein, wherein thestimulus cylce is individualized to the user.

The wearable system of any embodiment disclosed herein, whereinindividualization of the stimulus cycle comprises receiving a user inputrelated to perceived stimulus of the skin surface.

The wearable system of any embodiment disclosed herein, whereinindividualization of the stimulus cylce is based on signals receivedfrom the blood volume sensor.

The wearable system of any embodiment disclosed herein, wherein thestimulus source comprises one of: a heating element or an environmentaltemperature.

The wearable system of any embodiment disclosed herein, wherein thehardware processor is configured to transmit an electronic message to afirst electronic system responsive to the determination of the anomalousbiologic event, said first electronic system configured toelectronically manage a home automation system.

The wearable system of any embodiment disclosed herein, wherein the homeautomation system comprises a door lock and wherein said electronicmessage is configured to instruct the first electronic system to unlockthe door lock.

The wearable system of any embodiment disclosed herein, wherein the homeautomation system comprises a home alarm system and wherein saidelectronic message is configured to instruct the first electronic systemto disable the home alarm system.

The wearable system of any embodiment disclosed herein, wherein the homeautomation system comprises a display and wherein said electronicmessage is configured to instruct the first electronic system to displayuser's medical information.

The wearable system of any embodiment disclosed herein, wherein themedical information comprises medication information and/or medicationregimen compliance.

The wearable system of any embodiment disclosed herein, wherein the homeautomation system comprises a display and wherein said electronicmessage is configured to instruct the first electronic system to displaystroke treatment user interface.

The wearable system of any embodiment disclosed herein, wherein the homeautomation system comprises a speaker system and wherein said electronicmessage is configured to instruct the first electronic system to triggeran audible alarm with the speaker system.

The wearable system of any embodiment disclosed herein, wherein thehardware processor is further configured to alert a third partycomputing system responsive to the determination of the anomalousbiologic event.

The wearable system of any embodiment disclosed herein, wherein thethird party computing system comprises an emergency service system.

The wearable system of any embodiment disclosed herein, wherein thethird party computing system comprises a clinician computing system.

The wearable system of any embodiment disclosed herein, wherein thehardware processor is further configured to initiate treatment protocolresponsive to the detection of anomalous biologic event.

The wearable system of any embodiment disclosed herein, furthercomprising a wearable treatment system and said treatment protocol isconfigured to activate the wearable treatment system.

The wearable system of any embodiment disclosed herein, wherein thewearable treatment system comprises an ultrasonic helmet.

The wearable system of any embodiment disclosed herein, wherein thewearable treatment system comprises a cooling gas delivery system.

The wearable system of any embodiment disclosed herein, wherein thewearable treatment system comprises a cooling helmet.

A system for detecting an anomalous biologic event in a person, thesystem comprising one or more of the following:

-   -   a first stimulus source configured to stimulate a first tissue        site on a right side of the person's body at a first time;    -   a second stimulus source configured to stimulate a second tissue        site on a left side of the person's body at a second time; and    -   one or more hardware processors configured to:    -   determine a first vasodilation response based on the stimulation        of the first tissue site;    -   determine a second vasodilation response based on the        stimulation of the second tissue site;    -   determine one or more differences in the first vasodilation        response and the second vasodilation response; and    -   detect an anomalous biologic event based on the determined one        or more differences in the first vasodilation response and the        second vasodilation response.

The system of any embodiment disclosed herein, wherein the firststimulus source comprises at least one or more of the following: a heatsource, a cooling source, or an electrical source.

The system of any embodiment disclosed herein, wherein the secondstimulus source comprises at least one or more of the following: a heatsource, a cooling source, or an electrical source.

The system of any embodiment disclosed herein, wherein the first time issynchronized with the second time.

The system of any embodiment disclosed herein, wherein the firstvasodilation response is determined based on a parameter responsive to ameasurement from a first blood volume sensor.

The system of any embodiment disclosed herein, wherein the secondvasodilation response is determined based on a parameter responsive to ameasurement from a second blood volume sensor.

The system of any embodiment disclosed herein, wherein the firstvasodilation response is determined based on a parameter responsive to ameasurement from an electrical activity sensor.

The system of any embodiment disclosed herein, wherein the secondvasodilation response is determined based on a parameter responsive to ameasurement from an electrical activity sensor.

The system of any embodiment disclosed herein, wherein the one or morehardware processors are further configured to determine a first baselinevasodilation response before the stimulation at the first tissue siteand determine a second baseline vasodilation response before thestimulation at the second tissue site.

A wearable system for detecting a stroke event in a person, the wearablesystem comprising one or more of the following:

-   -   a first wearable device configured to be in contact with a first        skin surface of a person, said first wearable device configured        to be secured to a left limb of the person, said first wearable        device comprising:    -   a first heat source in communication with the first skin        surface, wherein the first heat source is configured to heat the        first skin surface to a first target temperature;    -   a first skin temperature sensor configured to measure a first        temperature of the first skin surface; and    -   a first blood volume sensor configured to measure a first blood        volume at a first tissue site proximate to the first skin        surface;    -   a second wearable device configured to be in contact with a        second skin surface of the person, said second wearable device        configured to be secured to a right limb of the person, said        second wearable device comprising:    -   a second heat source in communication with the second skin        surface, wherein the second heat source is configured to heat        the second skin surface to a second target temperature;    -   a second skin temperature sensor configured to measure a second        temperature of the second skin surface; and    -   a second blood volume sensor configured to measure a second        blood volume at a second tissue site proximate to the second        skin surface; and    -   one or more hardware processors configured to:    -   receive a first baseline blood volume signal from the first        blood volume sensor;    -   receive a second baseline blood volume signal from the second        blood volume sensor;    -   output a first heating signal to the first heat source to        initiate a first heating cycle at a first time, wherein the        first heating cycle comprises heating the first skin surface to        the first target temperature;    -   receive a first post stimulation blood volume signal from the        first blood volume sensor in response to the first skin surface        reaching the first target temperature;    -   output a second heating signal to the second heat source to        initiate a second heating cycle at a second time, wherein the        second heating cycle comprises heating the second skin surface        to the second target temperature;    -   receive a second post stimulation blood volume signal from the        second blood volume sensor in response to the second skin        surface reaching the second target temperature; and    -   determine a stroke event based on the first baseline blood        volume signal, the second baseline blood volume signal, the        first post stimulation blood volume signal, and the second post        stimulation blood volume signal.

The wearable system of any embodiment disclosed herein, wherein thesecond post stimulation blood volume signal comprises a set of bloodvolume signals, such that the second blood volume of the second skinsurface is measured repeatedly before, during, and after a heating cycleof the second heat source.

The wearable system of any embodiment disclosed herein, wherein thesecond post stimulation blood volume signal comprises a plurality ofblood volume signals, such that the second blood volume of the secondskin surface is measured continuously before, during, and after aheating cycle of the second heat source.

The wearable system of any embodiment disclosed herein, wherein the oneor more hardware processors is further configured to calculate a firstbaseline ratio of alternating current (AC) to direct current (DC) forthe first baseline blood volume signal and a second baseline ratio of ACto DC for the second blood volume signal and to compare the firstbaseline ratio to the second baseline ratio.

The wearable system of any embodiment disclosed herein, wherein thefirst wearable device further comprises an environmental temperaturesensor.

The wearable system of any embodiment disclosed herein, furthercomprising a remote computing device communicative coupled to the firstwearable device and the second wearable device.

The wearable system of any embodiment disclosed herein, wherein theremote computing device comprises one of: a laptop, cellular device, aworkstation, a server, a desktop computer, a personal digital assistant,a second wearable system or device, or a netbook.

The wearable system of any embodiment disclosed herein, furthercomprising one or more electrodermal activity sensors.

The wearable system of any embodiment disclosed herein, wherein the oneor more electrodermal activity sensors are spaced apart from at leastone of the firest heat source or the second heat source by about 0.25inches to about 4 inches.

The wearable system of any embodiment disclosed herein, furthercomprising one or more motion sensors configured to measure a motion ofa body portion to which at least one of the first wearable device or thesecond wearable device is coupled.

The wearable system of any embodiment disclosed herein, furthercomprising at least one tensionable band coupled to the body.

The wearable system of any embodiment disclosed herein, wherein thefirst heat source is positioned concentrically about one or both of thefirst blood volume sensor and the first skin temperature sensor.

The wearable system of any embodiment disclosed herein, wherein thesecond heat source is positioned concentrically about one or both of thesecond blood volume sensor and the second skin temperature sensor.

The wearable system of any embodiment disclosed herein, wherein thefirst blood volume sensor comprises a photoplethysmography sensor or animpedance plethysmographic sensor.

The wearable system of any embodiment disclosed herein, wherein thesecond blood volume sensor comprises a photoplethysmography sensor or animpedance plethysmographic sensor.

The wearable system of any embodiment disclosed herein, wherein thefirst skin temperature sensor comprises a thermocouple, a resistancetemperature detector, a thermistor, or an infrared temperature sensor.

The wearable system of any embodiment disclosed herein, wherein thesecond skin temperature sensor comprises a thermocouple, a resistancetemperature detector, a thermistor, or an infrared temperature sensor.

The wearable system of any embodiment disclosed herein, wherein thefirst blood volume sensor is further configured to measure one or moreof: heart rate, heart rate variability, or oxygen saturation.

The wearable system of any embodiment disclosed herein, wherein thesecond blood volume sensor is further configured to measure one or moreof: heart rate, heart rate variability, or oxygen saturation.

The wearable system of any embodiment disclosed herein, wherein at leastone of the first target temperature or the second target temperature isindividualized to the user.

What is claimed is:
 1. A wearable system for detecting a stroke event ina person, the wearable system comprising: a first wearable deviceconfigured to be in contact with a first skin surface of a person, saidfirst wearable device configured to be secured to a left limb of theperson, said first wearable device comprising: a first heat source incommunication with the first skin surface, wherein the first heat sourceis configured to heat the first skin surface to a first offsettemperature, wherein the first offset temperature is a baseline skintemperature of the first skin surface plus about 1 degree to about 20degrees; a first skin temperature sensor configured to measure a firsttemperature of the first skin surface; and a first blood volume sensorconfigured to measure a first blood volume at a first tissue siteproximate to the first skin surface; a second wearable device configuredto be in contact with a second skin surface of the person, said secondwearable device configured to be secured to a right limb of the person,said second wearable device comprising: a second heat source incommunication with the second skin surface, wherein the second heatsource is configured to heat the second skin surface to a second offsettemperature, wherein the second offset temperature is a baseline skintemperature of the second skin surface plus about 1 degree to about 20degrees; a second skin temperature sensor configured to measure a secondtemperature of the second skin surface; and a second blood volume sensorconfigured to measure a second blood volume at a second tissue siteproximate to the second skin surface; and one or more hardwareprocessors communicatively coupled to the first and second wearabledevices and configured to: receive a first baseline blood volume signalfrom the first blood volume sensor; receive a second baseline bloodvolume signal from the second blood volume sensor; output a firstheating signal to the first heat source to initiate a first heatingcycle at a first time, wherein the first heating cycle comprises heatingthe first skin surface to the first offset temperature; receive a firstpost stimulation blood volume signal from the first blood volume sensorin response to the first skin surface reaching the first offsettemperature; output a second heating signal to the second heat source toinitiate a second heating cycle at a second time, wherein the secondheating cycle comprises heating the second skin surface to the secondoffset temperature and wherein the first time is synchronized with thesecond time; receive a second post stimulation blood volume signal fromthe second blood volume sensor in response to the second skin surfacereaching the second offset temperature; calculate a left-side differencebetween the first post stimulation blood volume signal and the firstbaseline blood volume signal; calculate a right-side difference betweenthe second post stimulation blood volume signal and the second baselineblood volume signal; compare the left-side difference to the right-sidedifference; and determine a stroke event based on the comparison.
 2. Thewearable system of claim 1, wherein the determination of the strokeevent is further based on stored reference data.
 3. The wearable systemof claim 1, wherein the one or more hardware processors are furtherconfigured to calculate a first baseline ratio of alternating current(AC) to direct current (DC) for the first baseline blood volume signaland a second baseline ratio of AC to DC for the second blood volumesignal and to compare the first baseline ratio to the second baselineratio.
 4. The wearable system of claim 1, wherein the first wearabledevice further comprises an environmental temperature sensor configuredto measure ambient temperature.
 5. The wearable system of claim 1,further comprising a remote computing device communicative coupled tothe first wearable device and the second wearable device.
 6. Thewearable system of claim 5, wherein the remote computing devicecomprises one of: a laptop, cellular device, a workstation, a server, adesktop computer, a personal digital assistant, a second wearable systemor device, or a netbook.
 7. The wearable system of claim 1, furthercomprising one or more electrodermal activity sensors.
 8. The wearablesystem of claim 7, wherein the one or more electrodermal activitysensors are spaced apart from at least one of the first heat source orthe second heat source by about 0.25 inches to about 4 inches.
 9. Thewearable system of claim 1, further comprising one or more motionsensors configured to measure a motion of a body portion to which atleast one of the first wearable device or the second wearable device iscoupled.
 10. The wearable system of claim 1, further comprising at leastone tensionable band coupled to the body.
 11. The wearable system ofclaim 1, wherein the first heat source is positioned concentricallyabout one or both of the first blood volume sensor and the first skintemperature sensor.
 12. The wearable system of claim 1, wherein thesecond heat source is positioned concentrically about one or both of thesecond blood volume sensor and the second skin temperature sensor. 13.The wearable system of claim 1, wherein the first blood volume sensorcomprises a photoplethysmography sensor or an impedance plethysmographicsensor.
 14. The wearable system of claim 1, wherein the first skintemperature sensor comprises a thermocouple, a resistance temperaturedetector, a thermistor, or an infrared temperature sensor.
 15. Thewearable system of claim 1, wherein the first blood volume sensor isfurther configured to measure one or more of: heart rate, heart ratevariability, or oxygen saturation.
 16. The wearable system of claim 1,wherein the second blood volume sensor is further configured to measureone or more of: heart rate, heart rate variability, or oxygensaturation.
 17. The wearable system of claim 1, wherein at least one ofthe first target temperature or the second target temperature isindividualized to the user.
 18. A method for detecting a stroke event ina person, the method comprising: securing a first wearable deviceconfigured to be in contact with a first skin surface of a person to aleft limb of the person, said first wearable device comprising a firststimulus source and a first sensor, wherein the first stimulus sourcecomprises a first heat source and the first sensor comprises a firstblood volume sensor; receiving a first baseline blood volume measurementfrom the first sensor; securing a second wearable device configured tobe in contact with a second skin surface of the person to a right limbof the person, said second wearable device comprising a second stimulussource and a second sensor, wherein the second stimulus source comprisesa second heat source and wherein the second sensor comprises a secondblood volume sensor; receiving a second baseline blood volumemeasurement from the second sensor; outputting a first stimulus signalto the first stimulus source to initiate an application of a firststimulus; receiving a first post stimulation response measured by thefirst sensor after the application of the first stimulus; outputting asecond stimulus signal to the second stimulus source to initiate anapplication of a second stimulus; receiving a second post stimulationresponse measured by the second sensor after the application of thesecond stimulus; calculate a left-side difference between the first poststimulation response and the first baseline blood volume measurement;calculate a right-side difference between the second post stimulationresponse and the second baseline blood volume measurement; anddetermining a stroke event based on the first response and the secondresponse a comparison of the left-side difference and the right-sidedifference.